The 'Methods for Designing Future Autonomous Systems' (MODAS) Project: Developing the Cab for a Highly Autonomous Truck

Abstract

Modern technologies have the potential to create a paradigm shift in the vehicle-driver relationship with advanced automation changing the driver role from “driving” to “supervising”. To design new driver environments that caters for these emerging technologies, traditional approaches identify current human and technical constraints to system efficiency and create solutions accordingly. However, there are two reasons why such approaches are limited within the technologically-evolving automotive domain. First, despite significant progress in the development of socio-technical systems theory and methods, the application of these methods is largely constrained to the existence of a current system. Second, there are few structured approaches for using the analysis results to support design. In MODAS, an attempt is made to overcome these challenges by developing and implementing a method for analyzing and designing a non-existent sociotechnical system—a highly autonomous truck. The starting point for MODAS is the Goals, Method, Observability, Controllability (GMOC) model (Sandblad, Andersson, Kauppi & Wikström, 2007). In MODAS we also consider safety in human-automation system interaction and identify suitable assessment methods via a systematic analyze of estimated situations, goals, actions and behaviors that are of high importance from a safety perspective. A summary of the project is provided.

Keywords: Autonomous vehicles, Cognitive Systems Engineering, Human Automation Interaction, GMOC

DOI: 10.54941/ahfe100670