Advances in Human Factors of Transportation

AHFE International

Accelerating Open Access Science in Human Factors Engineering and Human-Centered Computing

Advances in Human Factors of Transportation

book-cover

Editors: Gesa Praetorius, Steven Mallam, Amit Sharma, Dimitrios Ziakkas, Riccardo Patriarca

Topics: Transportation Engineering

Publication Date: 2025

ISBN: 978-1-964867-62-5

DOI: 10.54941/ahfe1005997

Articles

Investigating Relationships Between First Solo Hours and Overall Flight Training Performance for Part 141 Flight Students

Advancing to a professional pilot career involves successfully completing key flight training milestones, specifically obtaining the Private Pilot License (PPL), Instrument Rating (IR), and Commercial Pilot License (CPL). This study investigated how the number of flight hours needed to achieve the first solo flight correlates with overall flight training performance indicators, such as the total flight hours required to complete each licensing course and practical test outcomes, including whether students passed on the first attempt. Data from a Part 141 flight school in Florida was analyzed using Pearson and point-biserial correlations. Results showed significant linear relationships between first solo flight hours and the total flight hours needed across all three training courses, as well as a notable correlation with PPL practical test performance. The practical implication was discussed and future research was provided, including increasing the sample size and incorporating data from other flight schools, such as Part 61 institutions, to enhance the generalizability and accuracy of these findings.

Donghyun Yoo, Bill Deng Pan, Dennis Vincenz, Dahai Liu

Conference Proceedings

Some of our CVR data are missing: 92 airline accidents & incidents 2014–2024

In recent years there have been numerous accidents and incidents in which investigators could not retrieve pertinent cockpit voice recorder (CVR) data. As a result, the investigations were hindered and potentially valuable information was not passed on to the wider aviation community to prevent future accidents. Accident investigation agencies have repeatedly called for the introduction of long-duration CVRs to mitigate this problem. In 2021 the European Union introduced regulations requiring newly-manufactured aircraft weighing over 27,000 kg to be equipped with 25-hour CVRs, and in 2024 similar requirements were introduced in the United States. The aim of this paper is to draw attention to the extent of the “missing data” problem and gain a greater understanding of the reasons behind it. Building on previous studies (Cookson, 2019, 2023) the paper examines 92 safety events that occurred from 2014 to 2024. The events are coded according to: (1) CVR recording duration, (2) CVR information provided in the investigation report, and (3) the reason why data were not available. The study identifies 48 events in which the CVR was not promptly deactivated and/or there was a delay in notifying the investigating agency, and a smaller set of 12 events in which pertinent data were overwritten due to excessive flight time. The paper also highlights a worrying lack of standardization in the way in which CVR data are presented in accident and incident reports.

Simon Cookson

Conference Proceedings

Mayday, Mayday! - Is Heart Rate Variability a Suitable Objective Indicator to Detect Pilot’s Increased Mental Workload in Emergency Situations?

Human performance (HP) is a crucial factor in aviation, especially in high-cognitive-demand situations such as emergencies. This study explores the relationship between mental workload (MWL) and heart rate variability (HRV) in professional pilots, focusing on how these variables are influenced by different flight phases, pilot roles, and the implementation of an intelligent pilot assistance system (IPAS). Using a low-fidelity flight simulator, eight male pilots faced emergency scenarios, and their MWL was evaluated through subjective ratings. HRV was measured using the RMSSD parameter. Contrary to previous findings, this study’s results did not reveal a correlation between MWL and RMSSD. However, RMSSD values showed significant variation across flight phases, with the lowest RMSSD observed during critical decision-making processes in the FORDEC phase, rather than during the emergency phase. These results suggest that while RMSSD may not demonstrate a direct correlation with MWL, it remains a versatile and non-invasive method for monitoring physiological states. Implications for the use of HRV in real-life operations and the assessment of new assistance systems are discussed.

Giulia Troyer, Maria Hagl, Jörn Jakobi

Conference Proceedings

Investigating the Acceptance of Vertiport Construction Near Residence Using Technology Acceptance Model (TAM)

Unmanned Air Mobility (UAM) is an emerging concept of transportation expected to be integrated into urban areas in the coming years. Vertiports are essential facilities for operating UAM for locations where passengers board and disembark after traveling between destinations. This study examines public acceptance of vertiport construction in relation to annual household income and geographical location through a quantitative survey. The research adopts the Technology Acceptance Model (TAM) to investigate socio-economic and geographic differences in Urban Air Mobility (UAM) acceptance. It specifically assesses perceptions and tolerance levels concerning safety risks, noise disturbances, and privacy concerns related to vertiport implementation. Data were collected via an online survey comprising 19 questions addressing demographics and acceptance levels, with 64 responses obtained. A one-way ANOVA was conducted to analyze the public acceptance of UAM. The findings revealed significant differences in vertiport acceptance based on annual household income. Additionally, the study highlighted significant variations in the acceptance of privacy invasion, also associated with annual household income.

Hee Seon Yang, Bill Deng Pan, Dennis Vincenz, Dahai Liu

Conference Proceedings

Digital Assistant Concept for Enroute Air Traffic Management

Enroute Air Traffic Management in Sweden is facing both increasing air traffic and a predicted shortage of Air Traffic Management staff. Automation in the form of a Digital Enroute Air Traffic Management Assistant (DEMA) could support work by autonomously carrying out some tasks, while coordinating with and informing the Air Traffic Controller (ATCO), with sensitivity to current workload. This paper describes our DEMA concept, detailing how a digital assistant differs from automation in general, on a theoretical level. It also describes a set of operational concepts together with human-ai interaction and collaboration concepts. A sub-set of concepts were implemented in the UTM CITY Simulator as a high-fidelity prototype, so that the scenarios and DEMA interactions could be played out. To assess the DEMA concepts, a two-step procedure was carried out with a group of Air traffic controllers. First, a test session was carried out as a human-in-the-loop simulation, where they individually tested two situations where traffic could be delegated to DEMA. The participants then made individual reflections on DEMA, which they brought up in the subsequent workshop session on the same day as the test. During this workshop, the potential for DEMA in different settings, and alternative DEMA use cases were designed and discussed. The workshop ended with a new concept implemented as a testable prototype in the simulator.

Jonas Lundberg, Karl Johan Klang, Gustaf Söderholm, Karljohan Lundin Palmerius, Gustaf Fylkner, Björn Stavås, Magnus Bang

Conference Proceedings

Triggers and Consequences: A Multidimensional Analysis of the Rebound Effect in Sustainable Design

With advancements in technology and societal development, improvements in energy efficiency have heightened expectations for environmentally friendly sustainable products and services. However, sustainable design, despite its intention to reduce environmental burdens, often generates unintended negative consequences due to the rebound effect. Addressing the rebound effect within sustainable design is therefore critical to ensuring true sustainability. This study systematically investigates the factors within sustainable design that contribute to the rebound effect, starting from the three dimensions of sustainable design: economic society and environment and focusing on the interplay between resource and energy efficiency, user behaviour, and overall consumption dynamics. The findings reveal that designers' decisions, often driven by technological optimization and user-centric goals, can unintentionally amplify resource consumption. Similarly, design processes lacking systemic foresight may overlook sociocultural impacts, while design outcomes, may encourage higher usage frequencies due to cost reductions. To mitigate these challenges, the study proposes a set of multidisciplinary strategies aimed at fostering a more holistic approach to sustainable design. Ultimately, it offers a robust framework for achieving economic, social, and environmental goals, ensuring that sustainable design truly fulfills its promise of creating a better future for all.

Yi Liu, Shunqing Jia, Huibin Lian

Conference Proceedings

User-Driven Strategies to Enhance Cockpit Comfort in New Energy Vehicles

As new energy vehicles become increasingly prevalent, cockpit comfort has emerged as a key factor in user experience. This study identifies and categorizes comfort-related factors into four main domains—acoustic, lighting, thermal, and human-computer interaction—based on literature review and user interviews, with 16 specific sub-factors. By applying subjective evaluation and entropy weighting methods, the relative importance of each factor is quantified. Results highlight the human-computer interaction environment, particularly voice interaction, as the most influential factor. Accordingly, this paper proposes a three-layered enhancement strategy: user-cognizant interface design for voice interaction, dynamically adjusting interaction and feedback models based on different scenarios, anthropomorphic voice interaction metaphors, which provide innovative ideas for the design of new energy vehicle cockpit comfort.

Tianxiong Wang, Weili Zhou, Long Liu, Jing Chen, Xian Gao, Tong Yu

Conference Proceedings

Flexible Human-Machine Collaboration: The Concept and Case Study of Lunar Surface Exploration Task

This paper focused on flexible human-machine collaboration in complex systems, which aims to explore all feasible or desired function allocation and collaboration solutions in the design. A three-level framework, including labour division, mutual assistance, and joint performance, is proposed to help flexible human-machine collaboration analysis. Then this study illustrates the above concept and idea with a lunar surface sampling case study, including task decomposition, analysis of human and machine capabilities for each functional unit, and determining collaboration solutions and their applicable situations. These solutions enable dynamic function allocation, enhancing system adaptability and inspiring future human-machine system designs for lunar exploration.

Yanrong Huang, Manrong She, Chunhui Wang, Chao Zhu, Shanguang Chen, Zhizhong Li

Conference Proceedings

Flight Safety - Alcohol Detection assisted by AI Facial Recognition Technology

The Federal Aviation Administration’s (FAA) “Bottle to Throttle” rule requires that a pilot may not use alcohol within 8 hours of a flight and cannot have a blood alcohol content above 0.04% to ensure safety. However, a pilot could still feel intoxicated, even after the 8-hour window has expired. Some studies have shown decrements in pilot performance after 10 hours of drinking alcohol using a flight simulator. According to the FAA, aviation employees performing safety-sensitive functions are subject to random alcohol testing. Usually, a screening test and a confirmation test are administered to determine a prohibited alcohol concentration of a pilot. When a screening test is above the allowed limit, a confirmation test is conducted after 15 minutes. If the test can be conducted in a rapid and accurate manner before all pilots’ flights, the probability that a pilot is still under influence of alcohol, or drugs will be dramatically reduced. This project aims to develop an AI facial recognition technique using Human-Centered Computing (HCC) to more accurately identify if the pilot is still under influence of alcohol, instead of using the uniformed standard of 0.04% blood alcohol that may not apply for each individual.Rationale1) Blood alcohol level has a strong negative relationship with cognitive/ flight performance. For example, if an individual pilot is under the influence of alcohol use, their cognitive performance will be significantly impacted, as well as their flight performance will be significantly impacted.2) If an individual pilot is under the influence of alcohol use, the associated minor characteristics expressed on their faces. Those characteristics may not be able to be identified by human beings but can be detected by the AI facial recognition technique using HCC.3) Considering heterogeneity, the uniformed standard of 0.04% blood alcohol after 8 hours from drinking may not accurately reflect each individual pilot’s readiness to fly. The trained AI can detect whether an individual pilot is still under the influence of alcohol, regardless of blood alcohol concentration, which can serve as a rapid census test to ensure pilots’ safety to fly.MethodologyTask 1: Train the AI classification model by publicly available datasets of alcohol users’ facial images. Data source: Collect publicly available datasets containing facial images of individuals in various states of alcohol consumption (sober, mildly intoxicated, and heavily intoxicated). Images will be preprocessed using facial landmark detection and attention-based image segmentation to isolate key regions such as the eyes, nose, mouth, and skin tone changes that are sensitive to alcohol-induced variations. Model training: A deep convolutional neural network will be trained to classify the images and learn the relationship between facial features and alcohol-induced influences.Task 2: Examine the AI Facial Recognition algorithm among healthy average people (n=20) before and after certain amount of alcoholic beverage consumption. Specifically, the cognitive performance will be examined through a series of cognitive tasks focusing on deductive reasoning, working memory, concentration, associate-learning and spatial planning. The data will be used to fine-tune the AI facial recognition algorithm to more accurately identify alcohol influence. Task 3: Examine the AI facial recognition algorithm among pilots using flight simulator. The parameters of performance will be extracted from the simulator both before and after pilots’ alcohol consumption (n=20). The data will be used to customize the AI algorithm to customize it to pilots’ readiness to fly.Experiment ProceduresFor an average person, the capability of absorbing alcohol is 0.015 g/100ml/hour. In most healthy people, blood circulates through the body in 90 seconds, thereby allowing alcohol to affect cognitive function immediately, but full effects of a drink are felt within 15 to 45 minutes depending on the speed of absorption. In both experimental, each participant will spend 0.5-hour drinking, so the blood alcohol concentration will be around 0.018 % when they start their performances. Since participants’ alcohol absorbing rate varies (e.g., some participants may consume refreshments when drinking), their blood alcohol concentration will also be detected at several time points during the experiment by an alcohol breathalyzer tester as a reference.Significance1) Using HCC AI facial recognition, the alcohol test can be conducted on all pilots by simply scanning their faces, which improves flight safety compared to traditional spot-checking approaches.2) the AI facial recognition can also serve as the census screening test, before confirmation test by breath-testing device.3) the technology can more accurately identify if the pilot is still under influence of alcohol use, instead using the uniformed standard of 0.04% blood alcohol may not apply for each individual.

Mingyi Wang, Shuzhen Luo, Chi-bok Lee, Andy Jaeyeon Jung, Joao Souza Dias Garcia, Yanbing Chen

Conference Proceedings

Safety and Human Factors Challenges of Aircraft Berths: Problem Analysis and Optimization Approaches

With the development of long-distance flight technology and the increasing demand for ultra-long-haul flights, ensuring passenger comfort and safety has become a critical challenge. Aircraft berth designs play a key role in addressing this issue. However, existing designs still exhibit limitations in safety, ergonomic adaptability, space utilization efficiency, and intelligence features. This study, through literature and case analysis, systematically examines the safety and human factors challenges in current aircraft berths, and examines the shortcomings of existing berth designs in collision protection, body support, spatial configuration, and intelligent integration. Based on the analysis, multi-dimensional optimization schemes are proposed to enhance berth safety, ergonomic adaptability, space utilization, and intelligent features. The findings contribute to the theoretical framework for intelligent cabin design, and explores innovative paths under the human-machine-environment model. This study provides insights for optimizing aircraft berth designs, ultimately improving passenger experience and safety in ultra-long-haul flights.

Can Yang, Pengyu Chen, Yunusi Padun, Huimin Hu, Junmin Du

Conference Proceedings

Exploring the Impact of Factors on Upper Limb Functional Space and Operational Efficiency: A Theoretical Analysis

Operators in transportation environments, such as aircraft cockpits and vehicle cabins, must perform high-precision tasks within constrained spaces. Understanding the factors impacting upper limb functional space and operational efficiency is essential for optimizing human-machine collaboration. This study follows PRISMA guidelines and systematically reviews literature from Scopus, Web of Science, and SpringerLink to examine the impact of posture, environmental conditions, and task demands. Results show that posture impacts functional space by affecting muscle load distribution, force transmission, and fatigue. Environmental conditions restrict visual input, joint mobility, and dexterity while influencing efficiency through vestibular perception, grip friction, and muscle activity. Task demands regulate interaction distance, movement strategies, and muscle load, optimizing efficiency via task complexity and coordination. Task demands determine optimal posture under specific conditions, while environmental factors modulate muscle load and strategies. Proper posture adjustments mitigate environmental constraints, whereas improper posture increases strain and task difficulty. These findings provide insights for optimizing cockpit and cabin ergonomics. Future research should explore individual differences and biomechanical factors to enhance ergonomic design and human-machine collaboration.

Pengyu Chen, Yunusi Padun, Can Yang, Huimin Hu, Junmin Du

Conference Proceedings

The Implementation of AI in Aviation Accidents Investigations

Accident investigation is fundamental to aviation safety, serving to identify causal factors and prevent the recurrence of accidents. Traditionally, such investigations have depended on systematic methodologies like the SHELL model and Fault Tree Analysis, drawing on data from flight data recorders, cockpit voice recorders, and eyewitness accounts. However, the rapid integration of digital technologies, the increasing complexity of modern systems, and the challenges posed by globalized operations have created an urgent need for more sophisticated investigative tools. Artificial intelligence offers capabilities such as pattern recognition, predictive modeling, and real-time data analysis, which can significantly augment the investigative process and improve outcomes. This research explores the application of AI in aviation accident investigations with a specific focus on several areas. First, the literature review examines the use of AI for human error analysis, investigating behavioral patterns, decision-making processes, and cognitive workload during incidents. It also evaluates the potential of AI tools to assess system reliability by detecting latent failures and interdependencies in avionics and mechanical systems. Furthermore, the research considers how AI-driven applications - simulations can be used for resilience modeling by reconstructing accidents and assessing system responses to cascading failures. In addition, the study evaluates how AI can enhance investigative efficiency through the automation of data sorting, analysis, and hypothesis testing. A multi-disciplinary approach was employed, integrating theoretical frameworks with AI-driven simulations and case study analyses. The methodology began with an extensive literature review of existing accident investigation methodologies, emphasizing the role of technology and data analytics. Building on this review, an AI-powered investigative framework was developed that incorporates machine learning algorithms for anomaly detection, natural language processing for analyzing cockpit communications and maintenance logs, and predictive analytics for modeling potential accident scenarios based on historical data. The framework was then tested through the “Aviation Human Factors Analyst” Open AI application simulations that replicated past aviation accidents to validate its ability to identify causal factors and suggest preventive measures. Finally, the framework was applied to real-world aviation accidents, such as controlled flight into terrain and loss of control in flight, to assess its effectiveness in uncovering human, technical, and environmental contributors. By augmenting traditional methodologies with advanced AI-driven tools, investigators can achieve greater accuracy and efficiency in uncovering causal factors, ultimately enhancing overall aviation safety. Future research should address cybersecurity considerations to protect AI systems from cyber threats, explore the transferability of AI frameworks to other transportation sectors such as rail and maritime, develop AI tools capable of real-time incident analysis to support immediate corrective actions, and advance methods in explainable AI to ensure transparency and accountability in AI-driven findings. Integrating AI into aviation accident investigations promises a more resilient and adaptive safety ecosystem, paving the way for safer skies.

Gustavo Sanchez Cortes, Dimitrios Ziakkas, Debra Henneberry

Conference Proceedings

Improving Operational Safety by Leveraging the Structured Exploration of Complex Adaptation Framework

Traditional safety management often overlooks the nuances of human adaptation in complex socio-technical systems, from which derives a wealth of unexploited tacit knowledge. To demonstrate the usefulness of analyzing daily operation, this paper proposes an application of the Structured Exploration of Complex Adaptations (SECA) framework to proactively identify weak signals in everyday operations. Specifically, the framework consists in semi-structured interviews analyzed using the Grounded Theory (GT) method, supported by Large Language Models (LLMs), enabling deeper insights into everyday operations.

Adriana Dana Schmitz, Manuel Lombardi, Antonio Licu, Riccardo Patriarca

Conference Proceedings

The Implementation of AI in the eVTOL Safety Management Systems

The emergence of electric Vertical Take-Off and Landing (eVTOL) aircraft represents a transformative evolution in urban mobility, promising sustainable and efficient air transportation. However, the integration of eVTOLs into high-density urban environments introduces new safety challenges that require advanced Safety Management Systems (SMS). Traditional SMS frameworks, which rely on deterministic models and human-centric decision-making, are insufficient for managing the complexity of eVTOL operations. The integration of Artificial Intelligence (AI) into SMS offers a proactive approach to risk assessment, predictive maintenance, and human-machine interaction, ensuring enhanced operational safety and regulatory compliance. This study explores the role of AI in augmenting SMS for eVTOL operations, focusing on predictive analytics, human-machine interface (HMI) enhancements, and real-world applications from leading eVTOL manufacturers such as Joby Aviation and Lilium. AI-driven predictive analytics enable real-time risk detection and mitigation, improving component reliability and reducing maintenance-related failures. Enhanced HMI tools facilitate adaptive decision-making, reducing cognitive workload for pilots and optimizing safety-critical interactions between human operators and automated systems. Case studies demonstrate that AI-integrated SMS frameworks improve emergency response times, enhance situational awareness, and support the continuous evolution of safety protocols in eVTOL aviation. The findings of this study have significant implications for policy development, training programs, and collaborative innovation. Regulatory agencies such as the FAA and EASA must establish AI-driven safety regulations to ensure compliance while fostering technological advancements in urban air mobility. Training programs must be restructured to incorporate AI-based learning methodologies, preparing pilots and maintenance personnel for AI-enhanced workflows. Collaboration between AI developers, aviation regulators, and eVTOL manufacturers is essential to establishing standardized AI-driven safety management practices.As urban air mobility continues to expand, AI-driven SMS will play a critical role in ensuring the safety, efficiency, and scalability of eVTOL operations. The integration of AI into SMS provides a pathway for predictive, data-driven risk management, enabling a future where eVTOLs operate seamlessly within the global aviation ecosystem. Future research should focus on refining AI decision-making algorithms, improving real-time safety interventions, and developing regulatory frameworks that ensure the safe deployment of AI-driven eVTOL technologies.

Dimitrios Ziakkas, Konstantinos Pechlivanis, Debra Henneberry

Conference Proceedings

The role of Simulated Air Traffic Control Environment (SATCE) in the implementation of ICAO Level 4 requirements

The global aviation industry operates within an intricate framework of safety protocols, regulatory standards, and continuous performance enhancement measures. One critical area that has evolved significantly in recent years is the integration of the Simulated Air Traffic Control Environment (SATCE) in pilot and Air Traffic Control (ATC) training programs. SATCE offers immersive, realistic air traffic control scenarios, enhancing the competency of pilots and air traffic controllers in managing complex operational environments. This paper explores the pivotal role of SATCE in implementing the International Civil Aviation Organization (ICAO) Level 4 language proficiency requirements, focusing on enhancing communication, decision-making, and situational awareness skills. ICAO Level 4 language proficiency requirements were established to ensure that aviation professionals possess the necessary communication skills to operate safely and effectively in international airspace. These requirements emphasize communicating clearly, managing unexpected situations, and maintaining operational efficiency in diverse linguistic contexts. Integrating SATCE into training programs provides a dynamic platform for pilots and air traffic controllers to engage in authentic, high-fidelity communication exercises that mirror real-world scenarios. This paper employs a qualitative methodology grounded in Saunders' Research Onion framework, incorporating a thematic analysis of 30 peer-reviewed journal articles published between 2019 and 2024. The research focuses on SATCE applications, including the Advanced Simulation Technology Inc. (ASTi) Simulated Environment for Realistic ATC (SERA) system and the implementation of the Test of English for Aviation (TOEFA) method for pilots and air traffic controllers. The findings highlight the effectiveness of SATCE in fostering the competencies required by ICAO Level 4, particularly in enhancing Evidence-Based Training (EBT) and Competency-Based Training and Assessment (CBTA) frameworks. Through an in-depth analysis of SATCE's impact on pilot and air traffic controller training, this study identifies key themes related to adaptive learning environments, regulatory alignment, and technological innovation. The results underscore the importance of integrating SATCE into aviation training programs to support continuous improvement in communication proficiency, operational safety, and overall resilience. The paper concludes with recommendations for policymakers, training organizations, and industry stakeholders to optimize using SATCE to meet ICAO language proficiency standards and enhance global aviation safety.

William Aranda, Dimitrios Ziakkas, Debra Henneberry

Conference Proceedings

The Role of Simulated Air Traffic Control Environment (SATCE) in the Aviation Performance

The increasing complexity of modern air traffic control (ATC) environments necessitates advanced training methodologies to enhance operational safety and efficiency. Air Traffic Controllers (ATCOs) manage aircraft movements in highly dynamic and unpredictable airspaces, requiring high situational awareness, precise communication, and rapid decision-making skills. Given the direct impact of ATCO performance on aviation safety, there has been a growing emphasis on implementing Simulated Air Traffic Control Environment (SATCE) to support training, assessment, and operational proficiency. Communication competency is a fundamental aspect of ATC operations, as effective coordination between controllers and pilots ensures seamless air traffic management and reduces the risk of misinterpretations that may lead to incidents or accidents. Research has consistently identified communication errors as a leading cause of aviation accidents, with phraseology misinterpretation, language barriers, and stress-induced lapses being critical contributing factors (ICAO, 2022). SATCE provides a controlled highly realistic platform to enhance communication effectiveness by allowing ATCOs and pilots to practice standardized phraseology, manage complex operational scenarios, and refine their ability to convey clear, concise, and timely instructions under simulated high-stress conditions. Regulatory bodies such as the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) recognize the role of SATCE in developing ATCO proficiency and compliance with international safety standards. These regulatory endorsements underscore the necessity of SATCE in meeting global air traffic management safety objectives and aligning controller competencies with evolving operational demands (EASA, 2022). The implementation of Artificial Intelligence (AI) and Machine Learning (ML) algorithms within SATCE systems enables the creation of adaptive training scenarios that dynamically adjust to an ATCO’s proficiency level, ensuring continuous skill development and minimizing learning plateaus (ASTi, 2023). In addition to civil aviation, SATCE has significant applications within military air traffic control environments. Global defense organizations, including the U.S. Air Force and NATO, have increasingly incorporated SATCE into ATCO training programs to enhance operational readiness and minimize the risks associated with high-stakes military aviation activities (NATO, 2021). This paper explores the critical role of SATCE in optimizing aviation performance by mitigating human error, enhancing communication efficiency, reinforcing system reliability, and ensuring compliance with international regulatory standards. By analyzing global applications of SATCE in both civil and military aviation contexts, this study highlights the transformative impact of simulation-based training in the evolving landscape of air traffic control.

Dimitrios Ziakkas, Neil Waterman, Anastasios Plioutsias

Conference Proceedings

The Role of Human Factors in the Certification of eVTOLs in the Artificial Intelligence (AI) Era

The emergence of electric Vertical Take-Off and Landing (eVTOL) aircraft represents a paradigm shift in urban air mobility, promising safer, more efficient, and environmentally sustainable transportation. As the eVTOL industry progresses toward commercial deployment, certification processes have become a critical bottleneck, especially as they integrate advanced technologies such as Artificial Intelligence (AI). While the focus often lies on the technical and operational aspects of eVTOL certification, human factors play an equally vital role in ensuring safety, reliability, and public acceptance in this transformative era of aviation. This paper explores the intersection of human factors and AI-driven technologies in the certification of eVTOLs, emphasizing their impact on pilot training, operational frameworks, human-machine interfaces, and regulatory compliance.eVTOL certification introduces unprecedented challenges due to integrating novel propulsion systems, automation technologies, and AI-powered decision-making tools. Unlike traditional aircraft, eVTOLs rely heavily on AI for functions such as autonomous flight, collision avoidance, and air traffic integration. These systems require rigorous evaluation for their technical soundness and compatibility with human operators and the broader airspace ecosystem.Human factors encompass the cognitive, psychological, and physiological aspects of human interaction with aviation systems and are integral to the certification process. The introduction of AI complicates these interactions, creating new demands on human performance and decision-making. Regulators such as the Federal Aviation Administration (FAA) and the European Aviation Safety Agency (EASA) have recognized the importance of addressing these human factors, as evidenced by their increasing focus on human-machine interaction and pilot workload management in certification criteria.AI-powered systems in eVTOLs fundamentally alter the human-machine interaction paradigm, necessitating the design of intuitive interfaces and effective control mechanisms. Pilots, whether operating manually or overseeing autonomous operations, must be able to understand and interact effectively with AI systems. Poorly designed interfaces can lead to information overload, misinterpretation, and operational errors, particularly in high-stress scenarios such as urban airspace congestion or adverse weather conditions.The certification process must evaluate the usability of these systems through rigorous human-in-the-loop testing, ensuring that pilots can interact with AI systems in a way that enhances situational awareness and decision-making. Human factors considerations include the layout of control panels, clarity of AI-generated alerts, and the transparency of AI decision-making processes. For instance, explainable AI (XAI) is emerging as a critical requirement, enabling pilots to understand the reasoning behind AI-driven actions, such as route adjustments or emergency maneuvers. Beyond regulatory compliance, addressing human factors is critical for gaining public acceptance of eVTOLs. Passengers must feel confident in the safety and reliability of these novel aircraft, particularly when AI is involved in their operation. Clear communication, robust safety protocols, and transparent certification processes can help build this trust. Human factors research plays a vital role in understanding and addressing passenger concerns, from designing comfortable and reassuring cabin environments to developing emergency response procedures.The certification of eVTOLs in the AI era requires a comprehensive approach that integrates human factors into every stage of the process. From human-machine interaction and pilot training to operational frameworks and regulatory compliance, addressing these factors is essential for ensuring this transformative technology's safety, reliability, and acceptance. As AI continues to shape aviation's future, human factors' role in certification will remain central to the successful deployment of eVTOLs, paving the way for a new era of urban air mobility.

Dimitrios Ziakkas, Debra Henneberry

Conference Proceedings

Can Drivers Construct Accurate Mental Models of Autopilot?

More car companies are working on integrating partial automated driving capabilities into their cars. Drivers can switch vehicle control to the automated system on designated highways by using partial automated driving mode. The system uses technologies like adaptive cruise control, lane centering, and driver-monitoring to guarantee that drivers stay attentive to the road while supervising the automation. The promise is that partial automated driving will increase road safety. Although the system can take over some driving tasks, it still needs human supervision and intervention, and it is restricted to designated highways. The system should be monitored by humans actively, with the intention of intervening when necessary. The level of trust drivers built into the system affects safe monitoring and taking back control when necessary. Creating the right level of trust in a system requires shaping a correct mental model of the system. To achieve this, it's necessary to comprehend how the system reacts in various scenarios. Our research analyzed the drivers' mental models of Tesla's autopilot in various situations that are likely to be confusing or have caused car accidents with Tesla in the past. The drivers were unfamiliar with autonomous driving and had no previous experience with adaptive cruise control.Method: We conducted an experiment with 10 individuals who drove Tesla S equipped with partial automation known as Autopilot for a week while commuting daily. The subjects took part in an open-ended interview at the end of the week to unfold their mental models. The interviews were recorded and transcribed for thematic analysis. Results: Although the majority of participants' initial mental models were in line with the system's capabilities, there are concerns about mental models related to Tesla autopilot limitations, particularly in city driving, based on our findings. Two safety-critical themes were identified in the interviews: misunderstandings of the autopilot's limitations and misunderstandings of the system's purpose. Misunderstandings regarding limitations included all statements and sub-themes indicating the participants' confusion about situations where Tesla's autopilot can't be used. Misunderstandings of the system purpose included statements expressing participants' misunderstanding of their monitoring role in autonomous systems as supervisors. Our findings suggest that new drivers should be trained in autonomous driving to increase safety.

Hugh Salehi, Daniel Mcgehee, John Gaspar, Cher Carney

Conference Proceedings

How Intensity-to-Capacity (IC) Ratios on Cycleways Impact Cyclists' Perceived Safety, Flow, and Comfort

As cities assess old and new cycleways to accommodate more cyclists, understanding the capacity limits of these paths has become crucial to sustainable growth. Cyclists’ safety, comfort, and flow determine these capacity limits, and traditionally, researchers have assessed them through on-site observations and surveys. This study introduces an alternative method, utilizing an off-site cycling simulator to investigate how increasing intensity-to-capacity (IC) ratios influence perceived safety, comfort, and flow on a high-capacity Antwerp cycleway. The key metric, IC ratios, assesses traffic volume, i.e., intensity, in relation to the estimated road capacity. Researchers tested three increased IC ratios compared to the current IC ratio of 0.269: 0.33 (mild: +22.68%), 0.51 (moderate: +89.59%), and 0.69 (high: +156.51%). Fourteen participants provided post-session feedback using Likert-scale questionnaires (1-5 scale). The results indicated that as the IC ratio increased, perceived safety and comfort declined, while flow interruptions became more frequent. Although the study did not identify a critical threshold where these factors significantly deterred cyclists, it is possible that the highest IC ratio tested was not sufficient to reveal such a point, though the methodology appears capable of detecting it at higher values. Notably, participant responses aligned with expectations, suggesting the simulator’s potential as a tool for analyzing IC ratios in future research. This methodology offers urban planners a controlled, off-site approach that provides flexibility and efficiency compared to traditional in situ studies, which lack controllability. Lastly, this methodology provides a way to analyze potential future high-intensity scenarios.

Alexander Van Gastel, Annemiek Awater, Daphne Mulkers, Lien Vancraenendonck, Vincent Vanderhaeghen, Stijn Verwulgen

Conference Proceedings

Vibration Exposure During Neonatal Patient Transport by Ground and Air Ambulance

Neonatal transport is often necessary when newborn patients require specialized medical care. In Ontario, Canada, a standardized Neonatal Patient Transport System (NPTS) is used to ensure consistency and interoperability across healthcare facilities. Whether transport is conducted via ground ambulance, fixed-wing, or rotary-wing air ambulances, the transport system and patient are subjected to unique, and often high, levels of vibration. Vibration is transmitted throughout the NPTS and interface systems such that the patients may experience a different ride quality than transport team members, pilots, or drivers. We have investigated the vibration amplitudes and spectra from 1-150 Hz at multiple locations (floor, NPTS, pilot/driver floor, and pilot/driver seat) within four different vehicles used for neonatal transportation in Ontario (one ground ambulance, one helicopter, and two fixed-wing aircraft). Kinematics were used to evaluate locations where sensors were not present during data collection. A low-frequency range of 1-20 Hz was used for comparison of measured and predicted results, to reduce noise in kinematic acceleration evaluation while focusing on the range of human body resonance. The largest amplitude vibrations were measured in the vertical direction in all vehicles, with the ground ambulance acceleration being greatest. Amplification of ground vehicle motion to the patient location was present across much of frequency range of interest, although the highest transmissibility occurred in the helicopter vertical direction at 10 Hz. The vibration in the air ambulances was heavily dominated by the rotor or propeller frequency, while in the ground ambulance it was more significant at low frequencies related to vehicle suspension. Differing response spectra suggest efforts to improve ride quality for patients may need to be tailored to the vehicle type, in order to prevent patient exposure to high amplitude vibration.

Keely Gibb, Michael Avarello, Patrick Kehoe, Andrew Law, Eric Chen, Eleanor Gerson, Kim Greenwood, Andrew Ibey, Jean Ngoie, Stephanie Redpath, Adrian Chan, James Green, Robert Langlois

Conference Proceedings

Optimized Visualization of Capacity Information in Public Transport Networks

The utilization of public transport vehicles is of growing interest to transport companies and public transport authorities. Against the backdrop of the transport transition, a targeted increase in capacity is necessary in order to meet the expected increase in demand. Transport companies and their authorities are faced with the challenge of recording the utilization of individual journeys and entire networks and, if necessary, making adjustments where capacities are already reaching their limits. The data required for this is often collected with the help of automatic passenger counting systems. However, the visualization of this data is rarely adapted to the actual applications required. This project presents a user-centric approach for the optimized visualization of utilization information. To this end, user workflows and available data are first analyzed. Based on the information obtained, individual use cases and a prototype for visualizing the data are developed. A final evaluation of the prototype rounds off the work.

Waldemar Titov, Sebastian Knopf, Thomas Schlegel

Conference Proceedings

Understanding Visually Impaired Tramway Passengers' Interaction with Public Transport Systems

The design of inclusive public transport services is crucial for the development of modern, barrier-free smart city infrastructures. This study investigates the socio-technical networks that shape the accessibility experiences of visually-impaired passengers using the tram system in Linz, Austria. Using Actor-Network Theory (ANT) as a theoretical framework, we investigate how agency is distributed between human and non-human actors in complex socio-technical networks, re-conceptualising accessibility as an emergent network property rather than a fixed infrastructure characteristic.Our mixed-methods approach combines shadowing observations with focus group discussions. The shadowing protocol documented visually impaired participants navigating the tram system, capturing their spatial navigation techniques, interactions with the physical infrastructure, use of technological aids, communication strategies, and responses to unexpected situations. The focus group, comprising seven visually-impaired persons with varying degrees of impairment and transport experience, provided complementary insights into user experiences, challenges, and adaptation strategies.The analysis revealed four predominant dimensions influencing accessibility outcomes: (1) Network Configuration—interactions between human actors (passengers, staff) and non-human actors (assistive devices, infrastructure) collectively determined accessibility success, with translation processes mediating between different network elements; (2) Mobility Patterns—regular users demonstrated sophisticated system knowledge, with some deliberately using public transport to develop navigational skills, highlighting the importance of mental models in system navigation; (3) Technology Integration—digital tools, such as mobility phone applications enabled independence while revealing varying levels of technological comfort; and (4) Warning Systems—participants emphasized the importance of the 'two-sense principle' for warnings, with directional audio and tactile feedback being particularly valuable.In addition, we revealed multiple additional dimensions relevant in this context. These include: accessibility barriers (physical, social, technical), sophisticated user adaptation strategies, significant infrastructure design implications, organisational policy implications, complex risk management approaches, and specialized spatial navigation techniques. These findings demonstrate that accessibility challenges arise from misalignments in socio-technical networks rather than from individual limitations.Our research has significant implications for public transport design: (1) technological innovations must take into account diverse user needs and existing adaptation strategies; (2) critical "obligatory passage points" such as platform-vehicle transitions represent systemic vulnerabilities that require focused attention; (3) varying levels of technological proficiency require flexible, adaptable interface designs; (4) directional warning signals significantly improve safety by facilitating spatial orientation; and (5) human assistance remains essential alongside technological improvements, with social interactions continuing to play a critical role in accessibility outcomes.This research contributes to the broader discourse on inclusive transport systems by highlighting accessibility as an emergent property of socio-technical networks, requiring integrated approaches combining technological and social solutions. Future research will explore how emerging technologies could further improve accessibility, taking into account potential risks of exclusion, and longitudinally examine how users' navigation strategies evolve over time.

Dominik Mimra, Dominik Kaar, Enrico Del Re, Novel Certad, Joshua Cherian Varughese, David Seibt, Cristina Olaverri-monreal

Conference Proceedings

Relationship between Gazing Characteristics and Conflict in Overtaking Selection Toward Pedestrian Ahead

This study investigates how the walking speed of a pedestrian ahead and aisle width influence conflict and gaze behavior during overtaking selection. The experiment employed a virtual environment with a head-mounted display (MetaQuest Pro/Meta) and an omnidirectional treadmill (Virtualizer Elite 2/Cyberith GmbH). The experiment involved 13 university students, who walked through three types of spaces in sequence: “Training Space,” “Reference Speed Measuring Space,” and “Analysis Space.” The analysis space consisted of 9 conditions, defined by three speed ratios (the ratio of the pedestrian ahead's walking speed to the participant's reference speed: 0.7, 0.8, and 0.9) and three aisle widths (2.5, 3.0, and 3.5 m). During walking, torso rotation angles and Yaw angles of gaze were measured to calculate three analytical indices: “Overtaking Rate,” “Overtaking Selection Time,” and “Gazing Dispersion.”The analysis of the overtaking rate suggested that action selections were likely made based on the relative magnitudes of the following burden (attributed to the speed ratio) and the overtaking burden (attributed to the aisle width), which were anticipated during walking. For overtaking selection time, the results indicated that the influence of the following burden varied depending on aisle width, with narrower aisle widths likely causing greater conflict in overtaking selections. Furthermore, for gazing dispersion, the findings suggested that the equilibrium between the following burden and the overtaking burden could influence the distribution of gaze.These findings represent a novel contribution by demonstrating the potential to quantify conflict due to action selection through gaze analysis. Based on these results, seamless measurement of anticipated burdens during action selection may become feasible.

Taisei Ogawa, Yohsuke Yoshioka

Conference Proceedings

Innovative Design of Detached Community Mobile Healthcare Emergency Vehicle System

In the urbanization process, the traditional emergency vehicle is exposed to insufficient response speed and efficiency in dealing with complex communities' environments, public health emergencies, and traffic congestion. Therefore, it is necessary to focus on the innovative design of the detached community mobile medical emergency vehicle system. Based on literature review, data collection and user requirements research, the existing community medical service and emergency vehicle systems are analyzed in depth, and a prototype model is developed based on the modularization concept. In cooperation with community health service centers, hospitals, and many other parties, the detached mobile medical emergency vehicle for communities integrates medical resources to form a multifaceted service system. It can deliver medical services to residents, flexibly adjust services, and carry out health education. the detached design expands the scope of first aid, and with the UAV form, it can cope with congestion. The system significantly shortens medical response time, improves service coverage and resource utilization, provides a good user experience, offers high potential for improving the quality and efficiency of emergency medical services in the community, and provides a new way of thinking for the development of medical emergency systems in the future.

Xin Chen, Wutian Chen

Conference Proceedings

Strategic objectives and data collection for regions implementing new mobility services

The aim of this study is to identify the outputs and outcomes of on-demand transport services that could lead to the implementation of these services in regions. We conducted an interview survey in the seven regions where demonstrations were carried out as part of the Smart Mobility Challenge in 2022. (The Ministry of Economy, Trade and Industry (METI) and the Ministry of Land, Infrastructure and Tourism (MLIT) had launched the Smart Mobility Challenge project since 2019.) The content of the interviews was based on the evaluation grid method. First, we asked about the benefits of the services expected to be provided by the demonstration. Then we asked, as a higher level concept, what good it would do for the region (ripple effect) and, as a lower level concept, how this could be measured (evaluation indicator). The results of the interviews were categorised into areas that have now moved from demonstration to implementation, areas that are still in the process of demonstration and areas that have now stopped demonstrating. As a result, we were able to identify the relationship between outcomes and evaluation indicators that could not move from demonstration to implementation and could not continue the demonstration.

Toshihisa Sato, Naohisa Hashimoto, Takafumi Ando, Takahiro Miura, Tran Viet

Conference Proceedings

Drivers’ Behavior while Interacting With E-Scooters in Urban Areas: An Assessment using Driving Simulation

E-scooters have become a popular mode of transportation in urban areas worldwide, offering mobility benefits and last-mile solutions while also presenting safety challenges related to increasing interactions between e-scooters and motor vehicles. This study used driving simulation to investigate driver behavior when interacting with e-scooters in diverse operating conditions replicating a two-lane urban street. Three conflict scenarios were examined: an e-scooter rider crossing at a crosswalk, an e-scooter rider crossing unexpectedly at mid-block from behind a parked vehicle, and e-scooters riding alongside traffic with and without bike lanes. Lateral position and speed profiles from twenty-four participants were analyzed in eight scenarios. Results indicate that 42% of drivers initially increased their speed to overtake the e-scooter but were often forced to slow down due to oncoming traffic. Speed behavior significantly varies depending on the presence of a bike lane on the street, with higher speeds observed in scenarios with the bike lane. Findings suggest that drivers may not always be aware of e-scooters and do not consistently drive safely, particularly in unexpected encounters. These insights underscore the need for safer design to protect both e-scooter riders and other road users. The results indicate that adding a bike lane enhances the safety of e-scooter riders.

Didier Valdés, Carol Perello, Alberto Figueroa, Ivette Cruzado, Angel Sanabria

Conference Proceedings

Advanced Driver Assistance Systems and Emotion-based Driver Behavior

Automobiles have evolved over the decades to include an increasing number of automated systems that assist the driver or even take over control of the vehicle. As a result, the human demands from vehicles have changed so that cognitive power can be used to participate in other activities while driving. These advanced drivers assistance systems (ADAS) include features such as lane keeping assistance, adaptive cruise control, blind spot monitoring and emergency crash avoidance. Each of these systems works to improve vehicle safety, principally by decreasing the required human intervention in some task (e.g., maintaining lane, emergency braking, etc.). ADAS portend the availability of fully self-driving vehicles and the promise of complete road safety. While ADAS have helped reduce the number of roadway collisions, they have not completely omitted the risk of a collision.Although Advanced Driver Assistance Systems (ADAS) have helped reduce driving risk, the control of the vehicle is still largely in the hands of a human driver, whose emotional state while driving could have a significant impact on their risk, and is in constant flux. Emotions have been proven to affect the driving habits of drivers, although the valence, magnitude and significance of impact depend on the individual. Addressing driving risk with ADAS, therefore, should focus on adapting to adverse emotional states. In this paper, we review the current understanding of emotion state development and evolution in drivers and their impact on behavior. Secondly, we review the current capabilities in advanced driver assistance systems. This work is the first part of a broader research effort aimed at developing ADAS that are capable of adapting to driver emotion state.Each emotion affects drivers performance differently through valence and significance. For example, the driving performance of someone experiencing anger is different than the driving performance of someone experiencing sadness. In these moments of extreme valence (positive or negative), driver performance is reduced and the potential for accidents is increased. In this paper, we review the current understanding of emotion state development and evolution in drivers and their impact on behavior. Secondly, we review the current capabilities in advanced driver assistance systems. This work is the first part of a broader research effort aimed at developing ADAS that are capable of adapting to driver emotion state.

Anthony Waters, Vincent Paglioni

Conference Proceedings

Motion sickness detection in autonomous vehicle with biosensors: A review

The advent of autonomous driving reduces human control and situational awareness on the road, significantly increasing the likelihood of motion sickness (MS) among passengers. This review explores key physiological measurement methods for detecting MS in autonomous vehicle environments, emphasizing the effectiveness of various biosensors—such as those monitoring body motion, brain activity, eye response, and heart rate. It highlights the potential of multi-sensor fusion methods to enhance sensor usability and provide comprehensive, real-time MS detection, ultimately improving passenger comfort.

Yaorun Zhang, Xu Sun, Yifan Yang, Juanfen Xu, Qingfeng Wang, Jiang Wu

Conference Proceedings

Elderly-friendly Design of In-vehicle Navigation Interface in New Energy Vehicles from the Perspective of Implicit Interaction

To enhance the user experience and safety of the interactive interface in new energy vehicles, this study explores the age-friendly design methods for the in-vehicle central control navigation interface from the perspective of implicit interaction. Through literature analysis and questionnaire surveys, factors influencing the age-friendliness of automotive interactive interfaces were obtained, and the influence weights of different factors were calculated using the entropy weight method. Based on the calculation results, key requirements were extracted from three aspects: interface layout, interface elements, and interaction feedback, and a practical age-friendly design plan for the central control navigation interface was further proposed. On this basis, elderly drivers were recruited to conduct simulated interaction experiments, and the completion time of navigation tasks was collected. By comparing the operational performance of the navigation interface under explicit and implicit interaction schemes, the usability of this plan was verified. The experimental results show that the central control navigation interface under implicit interaction can effectively shorten the interaction time and improve the interaction experience of elderly drivers. Based on this, this study proposes age-friendly design strategies for the central control interface from three aspects: multi-sensory design, simplification of the interface hierarchy structure, and adaptive adjustment of the interaction interface, thereby providing new theoretical references for the age-friendly design of new energy vehicle navigation interfaces.

Tianxiong Wang, Yuqi Han, Long Liu, Jing Chen, Xian Gao, Tong Yu

Conference Proceedings

Recognising driver anger using multiple physiological signals

Anger is particularly important to recognise accurately and effectively as the most important negative emotion affecting driving safety and the driving experience. In this study, five physiological signals, namely RESP, ECG, EDA, PPG and EMG, were combined to identify driving anger, in order to construct a multi-physiological emotion recognition model and establish the correspondence between emotion and physiological indicators. The data were collected from the simulated driving experimental environment. Firstly, happy emotion, angry emotion and neutral emotion, were induced by driving contextual video stimulus materials and non-driving contextual video stimulus materials, and the effects of the induced anger emotions were compared. Second, physiological sensors were used to collect the physiological data of the subjects under different emotions, the SAM scale was filled in to measure the degree of emotion evoked in the subjects, and then one-to-one correspondence between the subjects' emotions and physiological indexes was carried out, so as to construct the physiological and emotional data sample library. Finally, three algorithms, namely, decision tree, support vector machine and LightGBM, were used to process the collected physiological data to further classify and identify the emotions. The results show that the recognition accuracy of the classification task is improved by 4.43% on comparing with the results before feature selection, and this method verifies that it is feasible to use the LightGBM model as the emotion recognition model, which can provide the technical implementation basis for the emotion prediction and emotion regulation model in the subsequent research.

Ting Wei, Yong Liu

Conference Proceedings

Responses to and Recognition of Simultaneously-Occurring Driving Hazards using Auditory and Visual In-Vehicle Alerts

Proper allocation of attention while driving is imperative to safety. In-vehicle alerts, meant to signal towards potential hazards, can effectively direct driver attention. However, research on in-vehicle alerts has primarily been limited to single-hazard scenarios. Scenarios in which two hazards occur simultaneously may seem unlikely – yet at least a handful of impactful real-world conditions create such a scenario. An example could include making a right turn at an intersection when there is another car turning left into the same area (hazard 1) while a pedestrian is crossing the crosswalk (hazard 2).This study aims to better understand the impact that in-vehicle alert modalities have on driver attention towards simultaneously occurring road hazards. Specifically, measuring the effect of two different in-vehicle alert modalities (auditory and visual) on driver recognition of two simultaneous hazards across two experimental drives is undertaken. Brake response time, and responses to a post-drive situation awareness question are analyzed, along with the driver’s self-reported trust in the alert system, and experience with driving and alert systems (to identify any confounding effects).Participants were randomly assigned to one of two alert conditions, auditory or visual, where they were presented with the alert modality across two different hazard scenarios. The auditory alert consisted of three short tones through the simulator speaker system, on the higher end of the range recommended by NHSTA (Jeon et al., 2022). This alert was selected to signify urgency. The visual alert consisted of an image of a red circle flashing 3 times on the simulator screen and it was confirmed in pilot testing that it did not block any of the hazards as they occurred. The semantic meanings of the two alerts were balanced and meant to alert participants to the presence of a hazard without giving them specific directions. Study findings did not support the hypothesis that auditory alerts would be more effective than visual alerts in alerting drivers to both hazards in a scenario. An analysis of variance (ANOVA) conducted on responses to the hazard observance question showed that there was not a significant effect of condition on response accuracy. An exploratory analysis of verbally indicated hazard observance by type of hazard revealed an interesting pattern in which there was one hazard that was much more likely to be recognized by participants in each scenario. This pattern was likely due to hazard salience, where the more recognized hazard may have been more salient and therefore more likely to be recognized. This is also consistent with attentional blink, in which a hazard may have been more likely to be missed while appearing alongside another, more salient, hazard. Most driving research is limited to single hazard conditions. However, recent work has demonstrated the importance of multi-hazard study (Sall & Feng, 2019; Wan & Sarter, 2022). Our study adds to this limited area and suggests that additional research should be conducted to further understand the impacts of alert modality on drivers’ hazard observance, particularly simultaneously occurring hazards.

Morgan Mcalphin, Robert Gutzwiller, D'mitri Seymour

Conference Proceedings

A Vehicle Dashboard Dataset Towards Visual Complexity Design

With the expansion of the in-vehicle information system features, there are more and more new elements integrated into modern dashboards, which may lead to an increase in their visual complexity and additionally threatens drivers’ safety. To establish the cognitively efficient dashboards, protect driving safety and performance, it is essential for researchers and designers to identify what objective features increase the visual complexity of dashboard. However, due to various reasons, useful experiment materials of modern dashboards are rare for researchers and designers. To fill the gap, present study collected 1400 images of vehicle dashboards from 170 different brands online, then filtered, cropped the poor-quality images, and used the super-resolution technique to improve the images’ resolution with a self-made Python program. After pre-processing and evaluating objective visual complexity (OVC), present study recruited 160 participants to rate image’s subjective visual complexity (SVC), and finally form a vehicle dashboard dataset of 100 high-quality images with both SVC and OVC scores. Present study also conducted eye-track experiments to examine the validity of dataset. The result showed that 1) dashboards with high SVC would increase participants’ information searching time, deteriorate their searching accuracy; 2) In terms of gaze duration, top three influential objective features are: maps or vehicle state models, warning icons, chunks of information. In short, present study provide a useful vehicle dashboard dataset towards visual complexity design for researchers and designers, which may also be helpful for user-experience, ergonomics, or Human vehicle interaction research.

Zi-hao Liu, Zhizi Liu, Tao Chen, Liang Zhang

Conference Proceedings

Analysis of User Acceptance and Perception for External HMIs Based on Driving Situations

With the advancement of automated driving technology, the role of vehicle drivers is increasingly shifting to that of passengers, necessitating a transformation in non- automated verbal communication methods among road users. In this context, visual communication through external Human-Machine Interfaces (eHMIs) on automated driving vehicles has emerged as a critical area of focus. This study systematically analyses user preferences for eHMI messages across various driving scenarios (normal driving, single-lane roads, adverse weather, branching roads, and mixed traffic conditions) and user groups (drivers, pedestrians, and automated ride-hailing passengers). Additionally, it examines the influence of demographic factors such as age, as well as user understanding and favourability toward automated driving technologies, on message preferences. Data were collected through an online survey involving 900 licensed drivers, who were asked to rank the top three most useful eHMI message types for each scenario. The collected data were analysed using cross-tabulation and regression analysis to identify variations in message preferences across different variables. The findings reveal that preferred eHMI messages vary significantly depending on the driving scenario. For instance, messages such as “Informaion for Rear Driver,” “Intention to Proceed,” and “Emergency Alerts” were highly favoured in vehicle-related scenarios. In pedestrian-related contexts, the "Pedestrian Detected" message was deemed most important, while in ride-hailing situations, user identification and risk alert messages were recognized as critical. Although age-related differences in preferences were observed, their effect sizes were relatively small. Similarly, understanding and favourability toward automated driving technologies exerted modest influences in certain scenarios. Based on these findings, the study highlights the need for situation-specific eHMI designs, standardized interaction cues that promote mutual awareness, intuitive designs accommodating older adults, and adaptive systems capable of responding to dynamic driving contexts. To further validate these findings, future research will involve experimental studies to assess the applicability and effectiveness of these eHMI messages in real-world driving environments.

Yoonkyeong Kim, Sunhong Park

Conference Proceedings

Decision Making in Driving Moral Dilemmas: A Driving Simulator Study

Understanding how humans make decisions in dangerous driving situations, such as moral dilemmas, can provide valuable insights for assessing autonomous vehicles (AVs) and bridging the gap between AV algorithms and human morality. It is generally assumed that drivers will make utilitarian choices if given enough time, meaning their chosen actions align with their preferred actions. However, previous research has shown mixed results, especially under time and outcome pressure. This discrepancy between actual and preferred actions may be due to limited processing of the related events or reflexive reactions, such as turning to the right, particularly when data is collected from a single scenario. This study utilized a driving simulator to explore whether drivers make ethical decisions in programmed crash scenarios, collecting data from multiple scenarios. Thirty-one undergraduates participated using a STISM driving simulator to respond to driving moral dilemmas. The results indicated that allowing more time to process driving environments led to a higher percentage of utilitarian choices. Additionally, participants showed a preference for responding right over left. Impulsiveness did not affect utilitarian choices. These findings have potential implications for the regulation of driver assistance technologies and AVs.

Dongyuan Wang, Jacqueline Miller, Pingying Zhang

Conference Proceedings

Brand Perception and Trust in Autonomous Vehicle Brands in Japan

While autonomous driving technology is expected to become a new mobility, brand trust, and image play an important role in users. In this study, we aimed to clarify the trust and image of specific AV brands and users. We surveyed 25 brands from Asia, Europe, and the U.S. to investigate the impact of trust, brand image, and word images. As a result, Japanese companies were ranked as the most trusted brands, and brand recognition greatly impacted trust. In addition, brands with low recognition are less likely to gain trust, and differences in brand image are also related to trust. From there, we concluded the following: (1) Japanese companies are highly trusted in AVs manufacturing. (2) Higher brand recognition correlates with greater trust, as participants were likelier to trust brands they recognized well. (3) Words like "honest," "responsible," and "trustworthy" were strongly linked to trusted brands.

Sakura Akahoshi, Kengo Shintani, Yota Sekiguchi, Tomoya Sakata, Samuel Sanjaya, Makoto Itoh

Conference Proceedings

Operating in the Unknown – The Difference in Remote Operators' Attitudes Based on Their Knowledge of the Task at Hand

Remotely operated vehicles are predicted to bridge the gap between conventional and autonomous vehicles. However, there are still issues to address before the technology can be fully implemented on public roads. One being how the introduction of system latency affects remote operators in different driving conditions and potentially hazardous situations. In this paper, an analysis is made of the subjective rating result of four experiments (three simulator and one remotely operated vehicle experiments) where participants acted as remote operators in varied latency conditions. A total of 114 participants in three simulator experiments drove identical scenarios. Each scenario was driven with three latency conditions in experiment one and experiment three (baseline, +100ms and +200ms). Two different latency conditions (baseline and +150ms) were applied in experiment two. The latency conditions were masked for all participants, except for 26 who functioned as a control group in experiment three. Between each latency condition, rating data was collected through questionnaires regarding comfort, perceived control and realism of scenario. After the complete drive, participants were asked supplementary questions about their experience and differences between the latency conditions. In a fourth experiment, 18 participants drove a remotely operated vehicle on a track which included tasks such as line following, slalom driving, reverse parking and precision parking. Three latency conditions (baseline, +140 ms and +340 ms) were masked, and the same questionnaires were used as in the previous experiments. Rating data was compared between the experiments, as well as objective driving data collected by the simulators and the remote operation station. There seems to be a difference in attitude based on previous knowledge about the operators’ current driving conditions, though the actual driving performance is similar. I.e., unaware participants adapt their behavior to the same extent as aware participants. Unaware participants contribute any sense of difference to mental alertness, the state of the mechanical controls or a learning effect from recognizing the scenario between conditions. Aware participants contribute their performance to their ability to adapt their behavior based on the level of latency. Participants who noticed the change in latency without being told seem to have an increased sense of frustration, which shows the importance of clear and correct information to the operators. However, as the performance of the participants were deemed ‘good enough’, the main conclusion is that there is still a need for naturalistic studies concerning the use of remote operation in a real-world scenario.

Christian Jernberg, Jan Andersson

Conference Proceedings

How Does Adaptive Cruise Control Use Impact Driver Behaviors, Mental Models, and Trust and Perception in the System?

Adaptive Cruise Control (ACC), a system designed to support the vehicle’s longitudinal movement, maintaining a driver’s selected speed and gap between itself and the vehicle ahead, has been described and offered to drivers as a convenience system (e.g., McGehee et al., 2008), rather than as a safety system. Despite this description, ACC has the potential to have added safety benefits for the driver. This paper provides a review of the literature with respect to the current state of the research on the impact of ACC on human behavior related to driving and to examine the potential safety benefits, as well as current limitations, of ACC. We found that exposure and use of an ACC system impacts driver behavior, trust, understanding, and perception of ACC. Overall, research suggests that although ACC may have some safety benefits, these benefits can be contingent on how the individual uses or misuses the system.

Mary Aldugom, Sarah Izen, Iiona Scully, Christian Hoyos, David Cades

Conference Proceedings

The effect of AR HUD on enhancing the driver's trust in automated vehicles operation under high-risk scenarios

With the continuous development of intelligent vehicle technology, Augmented Reality Head Up Display (AR HUD), as a new type of human-machine interaction interface, is gradually being applied to automated vehicles. AR HUD provides drivers with intuitive, real-time driving information by seamlessly integrating virtual images with the real road environment, significantly improving driving safety and comfort. The guidance function of AR HUD can not only prompt obstacles, but also effectively reduce the cognitive burden during driving. This paper investigates the effect of AR HUD on the driver's interaction responses in emergency obstacle avoidance scenarios during automated driving mode. First, we built a Level 2 automated vehicle model in a driving simulator environment. A collision scenario was built between the automated vehicle and the motorcycle at the un-signaled intersection. Secondly, we developed three HMI information reminder modes for traffic conflicts during the automated driving operation, namely baseline type, risk-alert type, and AR HUD risk visualization type. 8 subjects were recruited to conduct our experiment to analyze what type of information presentation would give drivers more confidence to let the automated vehicle run autonomously without takeover when it driving in conflict scenarios.

Hongyu Hu, Yunhan Liang, Xinying Liang, Xuelian Zheng

Conference Proceedings

The Innovation Effect: How Futurism Shifts Risk Perception in Vehicles

Technology adoption models, such as UTAUT 2, focus on various technologies but might be too broad to effectively predict futuristic, highly innovative technology adoption. In this paper, we investigate potential futuristic technology adoption determinants and argue that perceived risk and time horizon (futurism) might play an important role. This study is a replication and extension of our previous study on the risk perception of futuristic vehicles, investigating the effects of different modes and autonomy levels of vehicles on risk perception. The study utilizes 3x3 mixed MANOVA design. The data was collected through an anonymous survey on students from a technical university. The results suggest that the futurism component of technology seems to lower perceived risk and that futuristic technology adoption may call for more tailored models that capture risk perception, familiarity, and expected exposure.

Hanna Neroj, Bruce Walker

Conference Proceedings

Exploring the Role of Predictability in Fostering Passenger Trust in Autonomous Ride-Hailing: A Case Study of Apollo Go

The integration of autonomous vehicles (AVs) into everyday life presents a significant challenge: fostering user trust. It is crucial to foster passenger trust in order to facilitate the acceptance and continued use of autonomous vehicles (AVs), particularly in the context of ride-hailing services such as Apollo Go. Users may be reluctant to utilise self-driving internet rides due to the absence of human supervision. Trust can be conceptualised as a belief in the safety, reliability, and predictability of self-driving cars. Among these attributes, predictability is of particular importance. Passengers are more likely to trust systems that are able to predict and understand their behaviour. This study examines the role of predictability in enhancing passenger trust in self-driving ride-hailing services, with Apollo Go serving as a case study.This study employs a methodology that integrates quantitative modelling with qualitative user studies. Quantitative data were gathered through controlled simulated driving. In a simulated driving environment, passengers experienced varying degrees of transparency in vehicle behaviour and decision-making processes. Qualitative data were collected through in-depth interviews and surveys to assess passenger trust in the predictability and transparency of self-driving cars. The core of the research methodology is to assess passengers' trust in vehicle behaviour, decision-making, and future actions under different levels of transparency.This study categorises transparency into three levels: basic behavioural transparency (e.g. real-time operations such as speed, braking, and cornering), situational decision-making transparency (understanding the rationale behind the decision), and predictive transparency (predicting the future behaviour of the vehicle). This layered model ensures that users have access to the appropriate level of information at the appropriate time, thus facilitating an intuitive understanding of the decision-making process for self-driving cars.The findings indicate that providing a transparent representation of the vehicle's behaviour and a predictable basis for decision-making, as well as future vehicle operations, can significantly enhance user perceptions of the safety and reliability of self-driving car systems. In particular, integrating predictive transparency increases passenger confidence in the vehicle's ability to handle complex situations, such as sudden stops or unforeseen roadway events. Additionally, the study demonstrated that higher perceived transparency was associated with lower passenger anxiety and higher levels of comfort.This study makes a contribution to the field by developing a framework that enhances passenger trust in self-driving ride-hailing services. It identifies the types of transparency that influence trust and provides insights for designing user-centred interfaces for self-driving cars. The findings emphasise the importance of predictability in improving user experience and trust, offering guidance for interface and system design for autonomous ride-hailing services.It should be noted that this study is not without limitations. Firstly, the study was conducted in a specific geographic area, which may limit the generalisability of the results. Secondly, the study focused primarily on transparency in driving behaviour and decision-making, and did not delve into other factors that influence trust, such as safety features or prior autonomous driving experiences.As autonomous vehicles become an integral part of the global transportation system, it is of the utmost importance to foster user awareness and trust. Transparent and predictable interaction mechanisms not only accelerate adoption but also enhance security, satisfaction, and long-term availability. This research presents practical insights for designing autonomous vehicle systems that enhance user confidence through a case study of Apollo Go. The findings emphasise the significance of transparent communication regarding vehicle behaviour and the assurance of seamless, predictable driving in order to promote passenger safety. Further research could extend these findings by exploring the long-term effects of trust-oriented design and examining how ongoing interactions affect user behaviour and acceptance. Additionally, incorporating cultural and demographic factors into personalised design strategies could enhance global adoption rates and meet the needs of diverse users.

Longyu Yuan

Conference Proceedings

The Interior Design of Research Demonstrators for Modular and Urban Last Mile Applications

Modularity is the smartest way to fit our vehicles to various specific needs optimizing on the materials, energy demand and user comfort. Therefore, we want to introduce human centered design approaches on our modular vehicle concepts: The Urban Modular Vehicle (UMV) and the U-Shift.The concept of the UMV vehicle family combines various derivatives for different use-cases. The UMV vehicle family consists of driver-controlled vehicles and automated movers for transporting people and goods.The UMV Peoplemover (PM) 2+2 is a derivative based on the UMV platform and is made for the automated transport for up to four occupants, which are sitting in a 2+2 vis-à-vis seat configuration. The Interieur of the UMV PM 2+2 includes luxury door covers with ambient light and four ergonomic singleseats with a large footwell. Because of swing doors that open on both sides without a conventional B-Pillar, there is a large entrance area. For the communication between the occupants and the vehicle and for the identification of passengers, there are displays implemented in the doors and below the roof.In addition to the UMV PM 2+2, there is the UMV Dualmover, which is intended for the combination of standing passenger and goods transport. Due to the different functions of this derivative, the interior can be customised to fit the needs of the current usecase. Due to the variable interior, the vehicle can transport standard package sizes and people with folding seats. Other derivatives with the same external dimensions as the Dualmover are the Peoplemover (large version), the Cargomover (large version) and the Hop On & Off, which is designed for very easy entry and exit.Another strategy for an electric, modular and automated concept is the U-Shift. It consists of the U-shaped Driveboard and different capsules as a loading unit. The Driveboard includes everything what is needed for (automated) driving like electrical drivetrain, steering, lifting system and automation system with sensors. With the lifting system, the Driveboard can lower itself, move into position, and the load the capsule via a rail system. The possibilities for capsule versions are infinite: passenger transport, cargo, garbage, supermarket, etc. The focus here will be the interior of a person capsule. Target was a prototypic but close-to-production implementation of a capsule for public transport. The seats are located on each side of the overhang of the capsule over the Driveboard, so there are three ergonomic seats left and right vis-à-vis and one at the front, orientated backwards. A space for a wheelchair is located in the rear end. This overhang allows an entrance on the right-hand side, which is equipped with a standard bus swing door and an automated ramp for wheelchairs. Big window areas ensure a good light incidence. In a workshop with disabled persons, some possibilities for improvement came up: Better positioning of door buttons, handrails at stairs, color highlighting of handrails, standard bus grabpoles, buttons with haptical feedback and seatbelts for every seat.Biggest difference to the first version is the implementation of a safety driver’s workplace. Due to security reasons, the safety driver has to stand in order to make it not too comfortable and ensure full attention. Only comfort is a motorized adjustable backrest. All the necessary input devices like joystick and control panel are arranged around the safety driver. Monitors on the left and right give him back view and view around the A-pillar.ReferencesU-Shift: https://www.dlr.de/de/fk/forschung-transfer/projekte/innovative-fahrzeugkonzepte/u-shiftUMV: https://www.dlr.de/de/fk/forschung-transfer/projekte/innovative-fahrzeugkonzepte/urban-modular-vehicle-umv Münster, Marco und Scheibe, Sebastian und Osebek, Manuel und Siefkes, Tjark (2022) Modulares Fahrzeugkonzept für die Mobilität von morgen. ATZ Automobiltechnische Zeitschrift (124), Seiten 16-21. Springer. doi: 10.1007/s35148-022-0906-4 <https://doi.org/10.1007/s35148-022-0906-4>. ISSN 0001-2785. Münster, Marco und Scheibe, Sebastian und Osebek, Manuel und Kopp, Gerhard und Hahn, Robert und Siefkes, Prof. Dr. Tjark (2022) Fahrzeugkonzepte für die Mobilität von morgen Vehicle concepts for the mobility of tomorrow. In: ATZlive Automatisiertes Fahren 2022. Springer. 8. Internationaler ATZ-Kongress: ATZlive Automatisiertes Fahren 2022, 2022-04-05 - 2022-04-06, Wiesbaden, Deutschland. Münster, Marco und Kopp, Gerhard und Friedrich, Horst und Siefkes, Tjark (2020) Autonomes Fahrzeugkonzept für den urbanen Verkehr der Zukunft. ATZ Automobiltechnische Zeitschrift, 122 (122), Seiten 26-31. Springer. doi: 10.1007/s35148-020-0216-7 <https://doi.org/10.1007/s35148-020-0216-7>. ISSN 0001-2785.

Sebastian Scheibe, Fabian Schmid, Marco Münster, Manuel Osebek, Gerhard Kopp, Tjark Siefkes

Conference Proceedings

Accessibility of Shared Automated Vehicles for the Visually Impaired Travelers

In this study, we conducted semi-structured interviews with 15 visually impaired individuals. We first explored their perspectives regarding their current travel behaviors and transportation experience. We then explored the potential of using Shared Automated Vehicles (SAVs) to enhance their travel experiences and address their existing transportation challenges. Results of the first part of the study revealed that most participants primarily worked from home, while those who commute largely relied on public transit. For doctor's appointments, rideshare was the most common method of transportation followed by public transit and riding with family. Ridesharing also emerged as the dominant mode of transportation for other essential activities such as visiting family, socializing, attending events, or work-related travel. Results of the second part of the study revealed a range of expectations and concerns related to SAVs, particularly in the areas of accessibility, safety, communication, and affordability. Most participants expressed enthusiasm for the potential benefits of SAVs to increase independence and access to underserved areas. They also highlighted critical accessibility needs, such as reliable means to identify assigned vehicles, accurate drop-off locations, and accessible interfaces. Affordability emerged as the key factor influencing potential adoption, with many participants indicating a preference for SAVs if they were priced competitively with existing transportation options, especially in comparison with traditional rideshare services. Findings of this study provide valuable insights for policymakers, transportation planners, and SAV developers to ensure that future automated transportation solutions are fully inclusive and meet the diverse needs of all visually impaired travelers.

Pei Wang, Benjamin Yi

Conference Proceedings

Effects of transparency and message framing on drivers' subjective perceptions and behaviors during takeover requests: An information design-based perspective

With the advancement of advanced driver assistance systems (ADAS) technology, understanding drivers’ responses to takeover requests is crucial for ensuring safety and operational efficiency when driving with ADAS. However, existing research mainly focused on providing information through different modalities (e.g., visual or audial), while the combined effects of transparency and message framing on drivers' perception and behaviors when faced with takeover requests have not been thoroughly explored from an information design-based perspective. This study aimed to investigate the combined effects of transparency (i.e., transparent vs. not transparent) and message framing (i.e., gain vs. loss) on drivers’ perceptions of designed information and behaviors (takeover time, emotional reaction, and message attitude) during takeover requests. Thus, the experiment employed a 2×2 within-subject design, with 31 participants (i.e., 23 females and 8 males) completing a driving simulator study featuring four distinct message prompts. The results indicated that: (1) The transparency significantly impacts drivers’ takeover performance, with longer takeover time observed when the information is not transparent; (2) The message framing significantly influences drivers’ emotional reactions, in which loss-framed messages evoke stronger emotional reactions compared to gain-framed messages; (3) Both the transparency and message framing significantly influence drivers’ attitudes towards the designed messages. More specifically, transparent messages generally result in more positive attitudes, while gain-framed messages consistently lead to higher message attitudes compared to loss-framed messages. The findings of this study underscore the critical role of transparency and message framing in enhancing the safety of drivers when driving with ADAS, which could be used to guide the design of human-machine interaction interfaces, foster drivers’ acceptance of ADAS, and further calibrate drivers’ mental models of and trust in ADAS.

Shuming Zhang, Yu Peng, Chunxi Huang, Tan Hao

Conference Proceedings

Design and Development of a Tactile Takeover Warning System Using a Tactile Seat for Automated Driving

Designing an effective takeover warning system is crucial for driving safety in conditionally automated vehicles. Given the advantages of the tactile modality in presenting takeover requests (TORs), this study designed and developed a seat-based tactile takeover warning system. A directional tactile TOR was used to instruct drivers on how to respond in various takeover scenarios. Additionally, the urgency of the tactile TOR was dynamically mapped to the time to collision with the hazard ahead, helping drivers perceive their proximity to the hazard. To evaluate the effectiveness of this novel takeover warning system, we recruited 24 participants and conducted a simulated driving study under varying levels of takeover event urgency and weather conditions. The results indicated that the developed tactile takeover warning system significantly reduced drivers' takeover time, regardless of the urgency level or weather condition. Therefore, this system has strong potential to enhance takeover performance and merits adoption by relevant practitioners.

Jinlei Shi, Wei Zhang, Hao Fan, Chunlei Chai

Conference Proceedings

Assessing Cognitive Workload and Driver Performance: A Comparative Study of Pneumatic and Vibrotactile Haptic Alerts for Takeover Requests in Autonomous Vehicles

This study explores the effectiveness of pneumatic and vibrotactile haptic feedback modalities on a steering wheel in improving driver response times and accuracy during Take-Over Requests (TOR) in Level 3 autonomous vehicles. Dual-modal feedback, combined with audio cues, was tested across nine TOR tasks to assess its impact on driver performance. Results show that combining audio with either feedback type significantly improved TOR performance compared to audio alone. Pneumatic feedback, offering a gentler and more naturalistic alert, enabled smoother transitions and reduced stress, while vibrotactile feedback, being more mechanical, may be better suited for high-urgency scenarios. Cognitive workload, measured using NASA-TLX scores, revealed that pneumatic feedback reduced mental demand and frustration more effectively than vibrotactile feedback. These findings suggest pneumatic feedback may be more comfortable for prolonged alerts, while vibrotactile feedback may be preferable in urgent situations. Further research could optimize adaptive feedback systems based on driving conditions.

Yang Liu, Zhegong Shangguan, Françoise Détienne, Stéphane Safin, Eric Lecolinet

Conference Proceedings

Decision Support System to Guide Use-Centric Cooperative, Connected and Automated Mobility Deployments: The SINFONICA Knowledge Map Explorer

The work presented is part of the SINFONICA project, funded by the EU, which aims to develop effective and innovative strategies, methods, and tools to engage users, providers, and stakeholders within the Cooperative, Connected, and Automated Mobility (CCAM) ecosystem. This includes citizens, particularly vulnerable users, transport operators, public administrations, service providers, researchers, and vehicle and technology suppliers. The objective is to systematically gather, understand, and organize their needs, desires, and concerns regarding CCAM in a way that is both manageable and actionable. SINFONICA will collaboratively create decision support tools, including the Knowledge Map Explorer (KME), specifically designed for designers and policymakers to facilitate the seamless and sustainable deployment of CCAM, ensuring inclusivity and equity for all citizens. This paper details the design, development, and architectural specifications of the SINFONICA KME, a tool that synthesizes and presents essential knowledge for CCAM solutions. The proposed tool utilizes an ontological structure that captures interactions and dependencies within the SINFONICA domain. The ontological framework is populated with data from interviews, focus groups, and workshops conducted in four different European contexts. For the SINFONICA project needs, the Protégé tool, an open-source ontology editor and knowledge management system, is employed. The transformation of structured data, like spreadsheets, into an ontology is streamlined using Cellfie, a tool within Protégé, facilitating the visualization and management of complex information. The tool is informed by data on user needs, preferences, concerns, and challenges, playing a crucial role in linking CCAM deployers, stakeholders, and users with tailored insights. The Knowledge Map Explorer acts as an intelligent navigation system, offering stakeholders specialized guidance on implementing CCAM solutions based on user type, context, and scenario. It leverages ontologies and expert-driven mapping, using tools like the Web Ontology Language (OWL) for structured representation. By employing a dual-system architecture—the Semantic-Based System and the Rule-Based System—this work specifies how the Knowledge Map Explorer will recommend best practices in CCAM based on explicit and inferred knowledge. The tool provides stakeholders with accessible, domain-specific insights, supporting the development of inclusive CCAM technologies. The system architecture specification translates the SINFONICA conceptual framework into a practical implementation plan. It specifies the technological components, integration strategies, and configuration settings required to achieve the objectives of the KME. Detailed in the document, the development of the backend system begins with a requirement analysis and specifications to identify core functionalities based on end-users' needs and user stories. Following this, the development of the Semantic-Based System is explained, and the implementation of the Rule-Based System is showcased, illustrating how predefined rules govern system behavior. Finally, the integration of the components is discussed, demonstrating how the semantic and rule-based systems are cohesively combined to deliver a unified solution that meets the specified requirements.

Anna Antonakopoulou, Konstantinos Fokeas, Evangelos Tsougiannis, Maria Krikochoriti, Angelos Amditis

Conference Proceedings

The Interaction Effects of Autonomous Vehicle Deceleration Style and eHMI Presence on Pedestrian Crossing Intentions

Communicating through external human-machine interfaces (eHMIs) is considered a potential solution to address the communication gaps and safety issues introduced by automated driving. This study investigates the impact of eHMI on pedestrian willingness to cross during the brief yet crucial 'deceleration-yield' process. Twenty-three participants experienced three different vehicle deceleration styles and two eHMI display conditions, including text-based eHMI and a baseline condition with no eHMI, through simulated videos portraying pedestrian scenarios. Participants continuously reported their real-time willingness to cross using an upward or downward swipe on a tablet and provided subjective assessments of anxiety and perceived risks through a questionnaire after each deceleration experience. The research findings indicate that a more aggressive deceleration approach decreases pedestrian willingness to cross, but the presence of eHMI can mitigate this effect. For pedestrians, the impact of eHMI is more pronounced when the vehicle's behavior exhibits its intent ambiguity. This study provides insights into scenarios where eHMI can be beneficial and offers design recommendations for eHMI implementation in real-world autonomous driving scenarios.

Shuwen Tian, Peiwen Luo, Zhengyu Tan

Conference Proceedings

Investigation and Analysis of Necessary Tasks and Responses for Unmanned Automated Bus in Challenging Situations

The bus driver shortage has become a social issue, particularly escalating in rural areas due to the labour shortage outside of urban regions. In order to solve these issues, Level 4 automated buses are expected. One of the key advantages of Level 4 automated buses is their potential for unmanned operation. To realize no drivers on a bus, remote surveillance is mandatory. For the introduction of level 4 automated bus service, the necessary tasks in both typical and emergency situations should be clear and the responses for these tasks should be defined. We already investigated the tasks typically performed by bus drivers by observing their actions from when a passenger boards and analysed the task by using bowtie analysis. By using these results, we discussed with bus driver and bus operation company about how to respond these tasks by considering the role, user acceptance and feasibility of the bus service because these three points should be considered for the introduction of automated bus service. In addition, the responses should be discussed with not only engineers in automated vehicles but also real bus driver and bus operation company staff. It is highly expected that these results and knowledge are important and beneficial for companies and local governments who would like to consider the introduction of level 4 automated bus services.

Naohisa Hashimoto, Yanbin Wu, Masaki Masuda, Toshihisa Sato

Conference Proceedings

Analysis of Subjective Sleepiness Considering the Influences of Driving Workload, Duration between Stations, and Driving Duration in Railway Driving

Railway drivers are required to maintain wakefulness while driving to confirm that the area in front of their vehicle is safe and to cope with extraordinary events. However, the driving environment, which includes being alone in the cab and performing monotonous tasks, tends to induce sleepiness. Therefore, in this study, we analyzed subjective sleepiness to investigate the relationship between drivers’ sleepiness and driving conditions. This study aimed to identify the influences that the driving workload, duration between stations, and driving duration have on drivers’ sleepiness.We used a railway driving simulator to conduct the experiment. Thirty males participated in our study. The participants drove in two ways: (1) the participants controlled the velocity of the simulated train, referred to as “high driving workload,” and (2) the system controlled the velocity of the simulated train, referred to as “low driving workload.” The durations between stations included the following three conditions: 1.5, 3.0, and 5.5 minutes. The duration of stopping at a station was 0.5 minutes. After practicing, the participants drove under six experimental conditions, consisting of a combination of two kinds of driving workload and three durations between stations. We randomized the order of the experimental conditions for each participant. The driving duration was 18 minutes per experimental condition. At every minute while driving, the participants were required to rate their subjective sleepiness using the Karolinska Sleepiness Scale, with the following grades: “Extremely alert” (score = 1) and “Extremely sleepy – fighting sleep” (score = 9).We conducted a multiple regression analysis in which the objective variable was the mean of the subjective sleepiness score, and the explanatory variables included the driving workload (high or low), the driving duration after stopping at a station (from 0 to 5 minutes), and the total driving duration (from 1 to 18 minutes).The results of the multiple regression analysis revealed that the score of subjective sleepiness was significantly associated with the driving workload, the driving duration after stopping at a station, and the total driving duration. The findings from the partial correlation coefficient indicated that with all other variables being constant, subjective sleepiness increased by 1.52 when the driving workload was low compared with when it was high. Subjective sleepiness also increased by 0.16 when the driving duration after stopping at a station increased by 1 minute. Furthermore, subjective sleepiness increased by 0.06 when the total driving duration increased by 1 minute. Additionally, the standardized partial regression coefficient showed that the driving workload had the largest influence among the three variables.With regard to the influence of driving workload, a previous study in the automobile industry showed that reducing driving workload caused “passive fatigue,” leading to sleepiness. Our results also showed that a low driving workload induced sleepiness. Furthermore, in terms of the effect of the driving duration after stopping at a station, another previous study in the automobile industry referenced “highway hypnosis,” whereby the monotony of the road environment tended to induce sleepiness. Our results showed that a long driving duration after stopping at a station was thought to be monotonous. Additionally, with regard to the total driving duration, the previous study indicated that the levels of sleepiness increased during driving. Our results also indicated that sleepiness increased with a longer driving durations.

Daisuke Suzuki, Chizuru Nakagawa, Hajime Akatsuka, Naohiro Akiu

Conference Proceedings

Human Factors in Accident and Incident Investigation and Reporting: A Framework for Understanding Human and System Errors in UK Railway Operations

The Office of Rail and Road (ORR) describe a signal passed at danger (SPAD) as an event that occurs when a train passes a stop signal when not allowed to do so (ORR, 2023). Over the past 100 years there have been several significant SPAD accidents including Harrow and Wealdstone (1952), Southall (1997) and Ladbroke Grove (1999). The driver of the train involved in the SPAD at Purley in 1989 was prosecuted as they were blamed for the event. Years later the driver was acquitted after new evidence showed that there had been 4 previous SPADs at that signal so there was something about the design of the infrastructure that made errors more likely (RSSB, 2018). This highlights that the human and system failures need to be understood to effectively manage SPAD risk. Harrison et al., 2022 compared data on how many SPADs occurred on the mainline network per year with data on red aspect approaches (RAATs) (RSSB, 2023) to show that train drivers have a SPAD event on average 1 in every 43,000 red aspect approaches. When compared to the human error probability for this task in the rail action reliability assessment tool (RARA) (RSSB, 2019), it showed that train drivers are performing close to the limit of human performance. System improvements will therefore be key in reducing the number and risk of SPADs.The number of SPADs each year and the risk from SPAD events decreased following the introduction of train protection warning system (TPWS) but has now plateaued at 250-300 events per year. According to the Safety Risk Model (RSSB, 2022), SPADs account for a low percentage of overall risk on the railway (RSSB, 2022), however there is still the potential for catastrophic harm where trains pass a signal at danger and reach a point where conflict with another train is likely.A framework has been introduced into the GB rail industry's safety management intelligence system (SMIS) to understand the causes of signal passed at danger (SPAD) events. This paper will:•Introduce RSSB’s human factors framework including the recent addition of categories to better understand and report incidents where distraction is a factor•Provide analysis of SPAD incident data over the past 3 years•Describe how the framework has been applied to drive safety improvements within the RSSB rail health and safety strategy (RHSS) industry groups such as the train accident risk group (TARG), rail investigation group (RIG) and the infrastructure safety leadership group (ISLG) with regard to high risk SPADs, improving rail investigation and response, and engineering works•Discuss the future of SMIS in terms of work carried out to support the integration of AI in the investigation and reporting process•Evaluate the next steps applying the framework to understanding how system and human error contributes to other railway operating incidents such as train overspeed and trespass across the GB rail network, in addition to describing the support provided in applying the framework through the revision of the rail industry standard RIS-3119-TOM: accident and incident investigation.

Tom Hyatt, Owen Mcculloch

Conference Proceedings

Design, Development, and Evaluation of a Crew Resource Management Learning Experience to Improve Freight Rail Safety

In 2015, the National Transportation Safety Board (NTSB) recommended that the Federal Railroad Administration (FRA) mandate Crew Resource Management (CRM) training for rail crews, based on CRM's proven success in reducing human error and enhancing safety in aviation. Recognizing parallels in the rail sector, and supported by recent FRA research (Rosenhand et al., 2012; Roth et al., 2013; Sebok et al., 2017), the rail industry stands to benefit from structured CRM training to improve communication, teamwork, and decision-making among train crews. Researchers at TiER1 Performance were engaged to investigate, develop, pilot, and assess a CRM training learning experience tailored to rail. This paper describes the design and development of a rail-industry CRM training prototype and discusses the results of a formative evaluation of the learning experience.

William Phillips, Angelia Sebok, Anna Grome

Conference Proceedings

On Track for Safety: Redefining Color Vision Standards in the U.S. Railway

The U.S. railway industry faces growing concerns due to an aging workforce and rising demand for skilled personnel, particularly in safety-critical roles like locomotive engineers and conductors. Recruitment efforts are further challenged by outdated color vision assessments mandated by the Federal Railroad Administration (FRA), which rely on tests such as Ishihara and Hardy-Rand-Ritter plates. These methods often fail to detect subtle or acquired color vision deficiencies (CVDs), overlook non-red-green variations, and do not reflect the visual demands of real-world railway environments, increasing the risk of signal misinterpretation, operational delays, and accidents. This paper reviews current federal regulations and compares railway vision testing practices with those in other safety-critical fields, such as aviation. It also explores alterative assessments such as computerized tools, virtual reality, and augmented reality to enhance diagnostic accuracy and consistency. Effective implementation will require regulatory updates, staff training, and sustained investment in research. Considerations of these advancements will allow the railway industry to better identify and manage CVDs, ultimately enhancing safety across railway operations.

Juksana Mai_Ngam, Zander N. Miller, Ainsley N. Bernard, Corey Gregory, Alex Chaparro

Conference Proceedings

Assessing Factors Influencing Transportation Choices in Taiwan

In 1997, the Swedish Parliament adopted Vision Zero, an ambitious traffic safety initiative aiming for zero fatalities or serious injuries within the road transportation system. This approach explicitly states that system designers are ultimately responsible for the design, management, and use of the road transport system, sharing responsibility for its overall safety. Road users are expected to adhere to the rules established by these designers. If users fail to comply due to lack of knowledge, acceptance, or ability, or if injuries occur, system designers must implement additional measures to prevent fatalities or serious injuries (Fahlquist, 2006).In recent years, traffic safety has become a key selling point, leading to a shift towards safety-driven development in the market. Car manufacturers now compete for top safety scores, and consumers base their purchasing decisions on these ratings. Public transportation by train or bus is generally safer than travel by car, and increasing public use of these modes can enhance overall safety, even if this improvement is not always reflected in the fatalities per mile driven. A U.S. national survey revealed that over 80 percent of respondents believe accidents are preventable, though fewer see them as predictable or under human control (Girasek, 2015). Despite road traffic injuries being a major cause of death for many years, the WHO emphasizes that most traffic incidents are both predictable and preventable (WHO, 2015). Similarly, the CDC recognizes 'improved global road safety' as a significant public health achievement (CDC, 2011).In Taiwan, a 2022 survey on public transportation usage revealed that the market share for public transportation was 14.3%, down from 16.0% in 2020, a decrease of 1.7%. The market share for private motor vehicles remained steady at 72.3%, while non-motorized vehicles (including walking, cycling, and electric scooters) reached a historical high of 13.4%, up 1.7% from 2020, with walking alone increasing by 1.5%. Among the various modes of transportation used for daily trips in 2022, motorcycles ranked highest (45.8%), followed by private cars (25.0%), walking (10.0%), bus services (6.0%), and rail transport (5.5%).To promote traffic safety, the Taiwanese government has introduced several policies to encourage the use of public transportation, but these efforts have been largely ineffective. Approximately 70% of the population still relies on private transportation as their primary mode of travel. This study aims to explore the critical factors influencing individuals' choices of transportation modes through a quantitative questionnaire survey. The study will use rating scales to assess users' perceptions of various transportation modes and traffic safety, considering factors such as practicality, convenience, cost, environmental impact, safety, and speed/time. At least 300 valid questionnaires will be collected for statistical analysis. The results are expected to provide preliminary insights into the key factors influencing transportation mode choices. Based on these findings, the study will offer recommendations to relevant authorities to improve public transportation service design, aiming to better meet travelers' needs and effectively change their transportation choices, thereby enhancing traffic safety.

Huang Fei-Hui

Conference Proceedings

Designing the interaction with Intelligent Decision Support Systems in Control Rooms: Challenges, Strategies, and Insights for Railway Applications

Control rooms are critical environments for monitoring and managing complex socio-technical systems across industries such as transportation, energy, and public safety. Decision Support Systems (DSS) play a pivotal role in assisting operators by processing vast amounts of data, streamlining decision-making processes, and reducing response times. The integration of AI into DSS, creating Intelligent DSS, introduces new challenges, particularly regarding explainability and trustworthiness. Operators must not only interpret complex AI-driven recommendations but also rely on them in high-stakes, time-critical scenarios. For instance, intelligent alarm management systems in railway control rooms are designed to help operators prioritize, filter, and manage alarm floods, reducing cognitive overload. However, their effectiveness heavily depends on aligning with operators' cognitive needs, maintaining situational awareness, and fostering trust in automated recommendations. This context presents new significant challenges for designing effective interactions between control room systems and operators, that differently for the back-end AI-based DSS solutions, remain less clearly defined. This gap complicates the development of clear strategies for ergonomic interaction design and their subsequent assessment. This study addresses these challenges through a systematic literature review, focusing on works within the domains of human factors and ergonomics. The review explores the following research questions: What are the main ergonomic issues identified in the current state of the art regarding operator interaction with Intelligent DSS in control rooms? What are the key interaction strategies proposed to address these issues, and what performance indicators have been identified? Performance indicators are defined operationally and accompanied by detailed methodologies for their calculation, ensuring their applicability to other design projects. These indicators include measures encompassing both objective and subjective aspects, related to situational awareness metrics, and trust in AI systems. By synthesizing research perspectives and providing actionable guidelines, this study offers a foundational reference for ergonomic design efforts in control room environments. It seeks to overcome current limitations and advance the development of safer, more efficient, and operator-friendly systems, with a particular focus on railway applications.

Laura Mancuso, Roberta Presta, Chiara Tancredi

Conference Proceedings

Non-standard work hours, accidents and injuries among seafarers. A systematic Review

Studies have shown that non-standard work hours are associated with an increased risk of accidents and injuries in healthcare, transportation and manufacturing sectors. Nevertheless, findings in Maritime work environment related to seafarers remain limited and inconsistent. To date, no meta-analytic synthesis has been published on this topic. We conducted a systematic review to examine whether exposure to non-standard work hours/shift work such as night shifts, extended work hours, rotation shifts is associated with an increased risk of accidents and injuries among seafarers. The study was registered in PROSPERO 2024 CRD42024543444.Methods: The review included 941 relevant original empirical studies from peer-reviewed electronic databases such as Ovid MEDLINE, PsycINFO, EMBASE and the Web of Science core collection using a predefined search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Inclusion criteria yielded only three (03) studies in the final review, which did not specifically study the relationship between non-standard work hours and the occurrence of injuries and accidents in seafarers.Results: Studies were largely registry based, cross-sectional studies and reported accidents and injury rates as key outcomes. The studies were from multiple counties, including the UK, Norway, Sweden, Canada, Poland, Philippine, Croatia, Indonesia, Spain, South Africa, German, Hongkong, Russia, Poland, China, Italy and Denmark. In the Great Britain, 36% of the deaths at sea were caused by accidents (95% CI: 19.8-34.7, N=1405) between 1979/80 and 1982/3, with a fatal accident rate in seafaring of 51.6 per 100,000 seafarer-years. Higher accident frequency occurred during night shifts (00:00-04:00) than during normal day hours and were related to work schedules and sleep deprivation. Injury rate varied from 6.31 per 1,000 (95%CI: 4.98-7.85) seafarers-years (4-year period) in Italy, 43.7 per 100,000 seafarer-years in the UK, to 40 per 1,000,000 work hours in a multi country study (11- countries). Conclusion: This review shows a high rate of accidents and injury among seafarers documented in various studies across the globe and suggests that these incidents are more frequent during non-standard work hours. However, studies directly associating non-standard work shifts with the occurrence of accidents and injuries among seafarers are scarce, warranting further research in this area.

Israel Nyarubeli, Bente Moen, Anette Harris, Ståle Pallesen, Erlend Sunde, Øystein Vedaa, Elise Victoria Tørdal, Bjørn Bjorvatn, Siri Waage

Conference Proceedings

Reframing Procedures and Teamwork for Man Overboard (MOB) Scenarios on Small MASS Passenger Ferries

The rise of Maritime Autonomous Surface Ships (MASS) requires reevaluating emergency procedures and teamwork dynamics. This study examines man overboard (MOB) emergencies on small passenger ferries, comparing a single onboard operator setup (baseline) to one including a Remote Operations Center (ROC) operator. Data from document reviews, observations, questionnaires, and interviews with three mariners revealed gaps between written procedures and actual practices due to contextual constraints and technological limitations. The ROC setup showed potential for task relief for the onboard operator but highlighted the need for enhanced technology and improved remote situational awareness. This study explores the impact of increasing automation, ROC integration, and reduced onboard manning on MOB procedures, teamwork, communication, and passengers, and discusses further work needed to maintain safety on small MASS ferries.

Staffan Bram, Nicole Costa, Victor Fabricius, Ted Sjöblom, Erik Nilsson

Conference Proceedings

Navigating Safety in the Maritime Sector: Developing Leadership Skills through Simulated Environments

The maritime industry is one of the most complex and high-risk sectors globally, where effective leadership is critical to ensuring safety, preventing accidents, and fostering a culture of continuous improvement. Given the dynamic and often hazardous nature of maritime operations, developing strong leadership skills is essential for both current and future maritime professionals. This paper explores the role of simulated environments in enhancing safety leadership within the maritime sector, with a focus on measuring human performance and the development of leadership skills. Simulators offer a unique advantage by providing realistic, risk-free experiences that help improve human performance and assess the characteristics of effective leadership.Today safety within a maritime organization is often evaluated through the safety climate and the Non-Technical Skills (NTS) of seafarers in the framework of proactive safety. NTS encompass the cognitive, social, and personal abilities that complement technical skills, and are visibly observable in safe behaviors aboard ships. Leadership is a key component of social NTS, both on real vessels and in simulated environments. The safety climate is assessed using questionnaires and interviews specifically designed for this purpose. To capture the NTS of seafarers working on Greek-owned vessels, an attitude questionnaire was distributed to a sample of 905 Greek seafarers at KESEN and 316 Filipino seafarers in Manila, as part of their training at Marine Educational Training (MET) centers. A total of 1,221 valid questionnaires were analyzed using factor analysis and related statistical tests to identify, assess, and classify NTS with a focus on leadership, and their impact on maritime safety.While traditional leadership training often relies on theoretical knowledge and classroom-based instruction, ship-based simulators bridge the gap between theory and practice by providing immersive, real-world scenarios. These simulations allow trainees to develop situational awareness, decision-making skills, and crisis management capabilities, all while reinforcing the importance of leadership in enhancing safety outcomes under pressure. This paper focuses on deck and engineering officers of Greek-owned vessels who participated in fire and evacuation simulations—such as firefighting, emergency response drills, search & rescue, and coordinated team tasks. These simulated exercises provide valuable insights into the challenges maritime leaders face and help them prepare for the unpredictable nature of real-world operations.This study examines the advantages of simulation-based training in developing key leadership competencies, including situational awareness, decision-making under stress, risk assessment, and team coordination. It also explores the impact of human limitations—such as fatigue and stress—on leadership effectiveness and human performance in extreme situations. Furthermore, the paper highlights the essential components of successful simulation-based leadership training programs, such as the use of firefighting and evacuation simulators, the integration of realistic scenarios, and the importance of feedback mechanisms that allow trainees to reflect on their actions and improve their skills.In conclusion, this paper argues that simulated environments are an invaluable tool for developing the leadership skills required to navigate the complexities of maritime safety. By integrating simulation-based training into leadership development programs, maritime organizations can cultivate a new generation of leaders who are better prepared to address the challenges of a high-risk industry and improve safety standards across the sector.

Georgios Lykos, Nikolaos Ventikos

Conference Proceedings

Human-Centered AI integration in nautical architecture: enhancing design processes through emotion recognition and intelligent systems

TThe landscape of naval design is undergoing a transformative revolution through the strategic integration of artificial intelligence, fundamentally reshaping the design process whilst preserving the central role of human creativity. This research, conducted at the University of Genoa, introduces an innovative "Emotional-Enhanced Design" paradigm that leverages advanced AI technologies to amplify designers' natural capabilities rather than replace them. The proposed methodology represents a significant departure from traditional design approaches, introducing a four-phase process that fundamentally reimagines how nautical design is conceived and executed. The first phase employs sophisticated emotion recognition technologies, integrating facial expression analysis, vocal tone evaluation through the Geneva Minimalistic Acoustic Parameter Set, and semantic sentiment analysis, enabling designers to gain unprecedented insights into client preferences and emotional responses. The second phase utilises an intelligent agent for comprehensive competitor analysis, automating the collection and organisation of market data through advanced web scraping techniques. The third phase integrates generative AI tools, such as MeshyAI, to rapidly transform initial sketches into 3D models, whilst the fourth phase implements virtual reality combined with biometric sensing for immersive design validation. Preliminary findings demonstrate remarkable advantages, including a 50% reduction in concept development time through automated competitor analysis and enhanced emotional understanding, and a 30% reduction in 3D modelling time through AI-assisted generation. The research demonstrates that the future of nautical design lies not in technological replacement, but in a harmonious collaboration between human creativity and artificial intelligence, where technology serves as an amplification tool for human expertise, particularly in understanding and responding to client needs. Future developments will focus on refining the virtual reality experience with advanced haptic technologies, implementing predictive user behaviour analysis, and developing a comprehensive knowledge base derived from accumulated project data. This approach represents a paradigmatic shift in understanding design as a deeply empathetic, technology-enhanced creative process that maintains the designer's central role whilst significantly improving efficiency and client satisfaction.

Laura Pagani, Paolo Gemelli, Alessandro Bertirotti, Mario Ivan Zignego

Conference Proceedings

A Systematic Curriculum Review of Ship Energy Efficiency Content Across Global Maritime Education and Training Institutions

The maritime industry is a significant contributor of total energy consumption worldwide and by extension, environmental impact. In the effort to transition towards more sustainable operations, a multifaceted approach is being taken to address energy management issues, new and alternative energy sources from regulatory, technological, and organizational applications. Seafarers, particularly deck officers and marine engineers, play a pivotal role in ship operations, managing and executing missions and onboard systems. The different aspects of energy utilization as related to maritime operations are continuously evolving for better efficiency and reduced impact on the environment therefore the seafarers who operate these systems require updated trainings with new and differing competencies and skillsets to ensure they are prepared for operating and maintaining these different systems. This may include, but not limited to, alternative energy sources, power generation and storage, fuel consumption estimation, energy consumption optimization, route and operation optimization, air pollution and resulting fuel residue. This paper investigates the extent to which maritime education and training (MET) institutions incorporate energy efficiency management into their curricula for seafarers. The primary goal of this paper is to determine the current education content, identify gaps, assess the readiness, and propose a pathway forward for MET institutions to better prepare current and future seafarers to implement energy efficiency strategies onboard ships.The review assessed the current state of training curriculum of deck officers and marine engineers across 69 maritime institutions from around the world which are members of the International Association of Maritime Universities (IAMU), assessing the integration of energy efficiency management into their marine engineering and nautical science programs. The online curriculum review revealed that 16% of the marine engineering programs included direct references to energy efficiency management, while 58% had no related courses listed. The remaining 22% had potential relevance to energy efficiency through courses on automation, ship design, environmental management; and 4% were related through the description of program results. For nautical science programs, the result showed even less relatable courses to energy efficiency management, with 7% of the reviewed programs including related courses. The majority (71%) had no relevant courses, while 19% were indirectly related through modules on environmental regulation or maritime law and 3% were related through the description of program results. The results of this curriculum review reveal lack of comprehensive energy management courses which may leave future seafarers unprepared to meet industry expectations or regulatory requirements once graduated. The global maritime industry’s regulator, the International Maritime Organization, has developed a number of relevant courses on the topics of climate change and shipping response, energy efficiency regulations and related guidelines, from management to operation, shipboard energy management, ship-port interface and energy efficiency, energy management plans and systems. These courses can serve as a guide for maritime institutions to develop effective modules and educational content on energy efficiency management and imbed more centrally within seafarer curricula. This initial mapping of current MET curricula on energy efficiency topics serves as a basis for further development of education and training program content within our research project to ultimately meet the evolving needs and demands of the industry, while ensuring MET institutions stay relevant and develop well equipped and skilled graduates to enter the industry.

Gift Bassey, Susan Ebaretonbofa-okonji, Kjetil Nordby, Etienne Gernez, Steven Mallam

Conference Proceedings

Customized maritime education and training path (C-path) for aspiring and current ship navigators

This study investigates the design and implementation of a Customized Maritime Education and Training Path (C-Path) for aspiring and current ship navigators by focusing on defining strategies to tailor learning paths to individual needs. Six customization strategies are compared and explored including 1) experience-based approaches that adapt training to students’ self-reported prior knowledge and 2) assessment-driven methods that use diagnostic tools to identify skill gaps and guide targeted instruction, 3) Interest-based customization allows students to align their training with personal career aspirations, while 4) pace-based strategies assumes all learners begin with the same foundational content but progress adaptively according to their individual learning speed. Additional two methods include 5) dynamic-performance customization, which uses real-time monitoring and adaptive algorithms to adjust training content based on learner ongoing performance, and 6) scenario-based customization which tailors learning through simulated real-world challenges. This study evaluates these approaches in terms of their effectiveness, feasibility and alignment with STCW and maritime industry standards, and we hope to present a customized learning path for modernizing maritime education to optimize skill acquisition, enhance safety and support professional growth in an evolving industry.

Tae-eun Kim, Gesa Praetorius, Ziaul Haque Munim

Conference Proceedings

Understanding Crew Estimations for Icebreaker Assistance in Ice-Covered Waters

In ice-covered waters merchant vessels often require assistance from icebreakers to avoid navigational hazards such as besetment and hull damage. Given that icebreakers are a limited resource, accurately estimating the need for assistance is crucial for the efficiency and safety of winter navigation. This estimation is non-trivial and involves several interconnected factors, including traffic restrictions, ice conditions, weather conditions, and vessel characteristics. Currently, icebreaker captains depend heavily on their experience to assess this need; however, there is a lack of understanding in how crews on board actually make these estimations. This study aims to present a clearer understanding of the estimation process used by crews. Employing the Critical Decision Method (CDM), we investigate the crew’s goals, the specific features they consider, and their ranking of these features in their estimation process. In-depth interviews were conducted with four participants with extensive seafaring experience, ranging from 15 to 43 years, and varying degrees of involvement in icebreaker operations, from 6 to 18 years. The analysis of the interviews reveals that despite variations among interviewees in feature rankings, there is consistency in identifying key influencing features. The resulting experience-driven key features and rankings are compared with data-driven analysis by Liu et al. (2024). Both methods identify ice conditions, such as ridged ice, as having a significant impact on estimations. However, interviewees place additional emphasis on vessel characteristics such as engine power. This comparison illustrates how experience-driven insights can enhance data-driven analysis which are often limited by the data quality and quantity. The outcomes of the study will contribute to the development of effective decision support tools for winter navigation.

Mashrura Musharraf, Cong Liu, Jennifer Smith

Conference Proceedings

Alternative Fuels for Shipping: Implications for Seafarers Occupational Safety and Health

The global shipping industry is already implementing a transition towards alternative fuels to reduce Greenhouse Gas emissions and improve its “environmental footprint”. This paper discusses the potential impact of a limited number of alternative fuels -namely hydrogen, ammonia and nuclear propulsion- on maritime transport workers and, more specifically, on seafarers’ Occupational Safety and Health (OSH), drawing on Sweden's experience with battery-fueled vessels. It is a self-explanatory fact that lithium-ion batteries offer benefits in emission reduction and operating efficiency; nonetheless, issues persist with OSH, regulatory frameworks, and infrastructure needs.Similarly, hydrogen and ammonia offer numerous potential benefits, but at the same time new hazards are also introduced. For example, hydrogen provides substantial energy density and zero carbon emissions, yet, it necessitates improvements in storage, delivery, and safety measures due to its flammability. Conversely, ammonia is more convenient for storage and transportation; nonetheless, it presents toxicity hazards and necessitates the establishment of stringent handling protocols. For its part, nuclear propulsion, historically regarded as a feasible choice for military ships and icebreakers, offers a compelling alternative for deep-sea shipping owing to its zero-emission characteristics and superior energy efficiency. However, significant issues such as nuclear safety, waste management, public acceptance, and regulatory obstacles continue to be challenging. Lessons learned from battery-powered shipping initiatives in Sweden and their implications for hydrogen, ammonia, or nuclear adoption can shed light on adopting alternative fuels, especially the inclusion of seafarers in a just energy transition. The analysis emphasizes the importance of legislative adaptation, the acquisition of seafarers to gain the proper training, skills, and competencies, risk assessment, and stakeholder involvement to ensure a safe and just transition for seafarers to alternative fuels. The results of this paper contribute to the ongoing debate about the global alternative fuel strategy within the maritime sector and their potential impact on maritime workers, underscoring the importance of rigorous safety protocols and international coordination to reach a low-carbon future for shipping by working on a sustainable maritime sector that also includes its key workers in the process of the transition.

Khanssa Lagdami, Dimitrios Dalaklis, Maximo Mejia Jr

Conference Proceedings

From ship to shore: Understanding Cognitive Challenges in Remote Pilotage Operations

Pilotage is one of the foremost safety measures provided by coastal states to ensure safe and efficient movement of vessels to ports. Pilotage is conducted by experienced navigators with expert knowledge of the local navigational landscape and traffic flows. Traditionally, pilots board a vessel and remain physically co-located with the ship’s bridge team throughout the operations. In recent years, several research projects have explored the possibility of remote pilotage, where the pilot can perform the same functions while being located on shore. These developments are largely driven by the technological advances enabling novel modes of communication and information exchange. In this study, we report findings from six semi-structured interviews with pilots who are being trained in remote pilotage operations in a Scandinavian port. The results highlight cognitive challenges that the participants experience as pilotage operations are reimagined to be conducted from a shore station. While this study is focused on pilotage, the identified challenges also highlight potential risks for and may inform the design of remote vessel control, e.g. for maritime autonomous surface ships.

Amit Sharma, Gesa Praetorius, Reto Weber, Scott N MacKinnon, Bjørn Sætrevik

Conference Proceedings

The Remote Support Centre – an Exploration of Technical Support and Coordination for Marine Archipelago Traffic

Three shipping companies for passenger traffic on the Swedish east and west coast took part in a participative design process generating seven scenarios during a research project from 2021-2024. The project addressed technical and operative challenges in setting up a Remote Support Centre (RSC) for marine archipelago traffic. One main technical challenge was to select among thousands of technical signals which can be transmitted from vessels, and decide which would be useful to send to a RSC. Using participative design in workshops and high-fidelity simulations, we identified needs and relevant parameters by recreating situations based on crew stories and experience. The RSC was installed in Stockholm, Sweden with three connected vessels. Our thesis - that marine archipelago traffic can be improved by making data available, processing and refining it, and delivered back to the onboard crew as decision assistance - was supported. Technical assistance from the RSC showed usefulness already in early live tests by enabling systematic checking of generators, alarms onboard, charging status of the batteries as well as initiating daily contact with the crew. The study also resulted in two tentative operative concepts for RSC services. Further development and testing of the concepts, exploration of useful information, design of RSC interfaces as well as assessment of economic aspects may be addressed in future studies.

Karl Johan Klang, Rickard Lindkvist, Jörgen Karlsson, Thomas Elwinger, Carl Westin, Jonas Lundberg

Conference Proceedings

Evaluation of a Digital Assistant concept for Vessel Traffic Service Operators

Vessel Traffic Service (VTS) is an information service for merchant vessels in areas with high traffic loads or in proximity to ports. VTS is provided by VTS operators (VTSOs) that synthesize a large amount of information from different screens and different information sources to choose when and what to transmit to the traffic in the VTS area. As recent technical advances have paved the way for new ways of interaction and collaboration between human operators and automation, the focus for future system design has shifted from operator in or on the loop to human-automation teaming. This study builds on these recent advances and presents findings from an evaluation of a concept for an advanced decision support tool, a Digital Assistant, for VTSOs. The digital assistant presents information and offers different options for interacting, such as acknowledging information or delegating certain tasks. Four expert users evaluated the system in Wizard of Oz demonstration. Overall, the users deemed the concept as having potential and being helpful in high workload situations. They interacted with and partially delegated tasks to the assistant system but also raised concerns about not always agreeing with the automation’s suggestions, nor understanding what information these were based on. While the approach seems promising, future system iterations should consider the timing of the interaction between operator and automation, and the access to information to enable VTSOs to trace the automation’s decision making and increase its transparency.

Gesa Praetorius, Jonas Lundberg, Karl Johan Klang, Anders Johannesson, Gustaf Söderholm, Magnus Bang

Conference Proceedings

Visual scanning strategies of maritime pilots during navigation

In maritime pilotage, the pilot operates the ship in cooperation with the bridge crew to ensure the ship’s safe passage through the route. In remote pilotage, the pilot does not enter the ship but works from a remote pilotage center (Grundmann et al., 2023). The latter has been studied in recent years as it offers many advantages compared to traditional pilotage, including being less dangerous for the pilots themselves and less costly. From a human factors perspective, remote pilotage presents significant challenges, as there is a risk that a remote pilot receives less information, potentially leading to reduced situational awareness. These challenges are related to changes in information sources, requiring the pilot to adapt from direct observation to relying on instruments and crew testimony. Such issues are critical, as problems with situational awareness are a common cause of maritime accidents in pilotage (Grech et al., 2002).To understand the potential problems in remote pilotage, the phases of ordinary pilotage should be well understood. Pilotage consists of several tasks such as route planning, master-pilot exchange, providing advice, ship navigation, communication and ship handling. In this study, we focus on navigation, where both the bridge crew and the pilot must maintain multiple types of situational awareness, including task, spatial, system, and social awareness. These can be further categorized into three levels: 1. Perception of the environment, 2. Comprehension of the situation, and 3. Projection of future status (Sharma et al., 2019). The types and levels of situational awareness are reflected in information requirements of pilot, which are indicated by the visual scanning of the environment.ObjectivesIn the current study, we aimed to understand the visual scanning strategies of maritime pilots operating in a simulator environment. Specifically, we sought to comprehend temporal changes in scanning strategies during different phases of navigation, enabling us to understand the information needs in various phases of navigation. This provides novel insights, as changes in visual scanning strategies have not been previously studied in maritime piloting.MethodsIn our study, each pilot and master navigated through a fairway in a simulator. Both participants were instructed to operate as they would in normal pilotage. The pilot wore a Pupil Labs Neon eye tracker, conversations were recorded with microphones, and actions were captured with two GoPro cameras. Additionally, actions were recorded in the simulator log files.DiscussionEye-tracking data revealed scan patterns that persisted throughout the route, as well as others that were specific to certain route phases, such as turning. The outside view was observed most frequently and was associated not only with understanding the ship’s direction and rate of turn but also with the pilot advising the master on current and upcoming navigational issues. A second significant finding was that the pilot confirmed commands by observing the master’s actions.Our study shows clearly why pilot-master cooperation is a sociotechnical system, where interaction with technology is intertwined with social interaction. An interesting challenge was how these social components could be maintained in remote pilotage, particularly in narrow archipelago routes where timely actions are critical.ReferencesGrech et al (2002). Human error in maritime operations: Analyses of accident reports using the leximancer tool. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 46(19), 1718–1721.Grundmann et al (2023). Use Case Remote Pilotage – Technology Overview. Journal of Physics: Conference Series, 2618(1), 012007.Haslbeck & Zhang (2017). I Spy with My Little Eye: Analysis of Airline Pilots’ Gaze Patterns in a Manual Instrument Flight Scenario. Applied Ergonomics 63: 62–71. Peysakhovich et al (2022). Classification of Flight Phases Based on Pilots’ Visual Scanning Strategies. In 2022 Symposium on Eye Tracking Research and Applications, 1–7. Seattle WA USA: ACM, 2022.Sharma et al (2019). Situation Awareness Information Requirements for Maritime Navigation: A Goal Directed Task Analysis. Safety Science 120, 745–52.

Jukka Häkkinen, Iiro Törmä, Jedi Seppänen, Lukas Ob De Beke, Mirva Salokorpi

Conference Proceedings

Enhancing Data Privacy in Maritime Operations with Federated Learning: A YOLOv7 Object Detection Approach

The maritime industry is currently experiencing a period of rapid transformation, driven by the integration of artificial intelligence (AI) technologies. This integration is enabling advancements in autonomous navigation systems, remote monitoring capabilities, and operational efficiency. However, these innovations are accompanied by substantial privacy challenges, particularly in the management of sensitive data collected from vessels. In this work, we propose a Federated Learning (FL) framework tailored for the maritime environment. This framework aims to address privacy concerns while leveraging the capabilities of AI. Utilizing the TUAS dataset, which contains images, and employing the YOLOv7 object detection model, we demonstrate how FL enables vessels to collaboratively train robust machine learning models without sharing raw data.Our approach ensures that data collected on vessels, such as images for navigation and object detection, remains onboard, thereby safeguarding sensitive information. Each vessel trains a local YOLOv7 model on its image dataset and shares encrypted model updates with a central server for aggregation. This global model is then disseminated back to the vessels, ensuring enhanced performance across the fleet without compromising data privacy. A comparison of our FL-based approach to traditional centralized training methods is presented, highlighting the trade-offs in model accuracy, privacy preservation, and communication overhead. The findings demonstrate that Federated Learning with YOLOv7 attains object detection performance that is competitive with other methods, while addressing privacy concerns by keeping raw image data localized. Integrating FL into the maritime industry provides a scalable and secure solution for AI-powered applications, ensuring data privacy while promoting innovation. Experimental results are a substantial contribution to the development of privacy-preserving AI solutions for autonomous maritime operations and remote monitoring, demonstrating FL's potential to transform the maritime industry.

Vo Ngoc Thy Thao Vo, Amin Majd, Mehdi Asadi, Juha Kalliovaara, Tero Jokela, Jarkko Paavola

Conference Proceedings