A Multimodal Sensor Setup for In Situ Comparison of Driving Dynamics, Physiological Responses and Passenger Comfort in Autonomous Vehicles

Abstract

With the growing integration of automated driving (AD) functions in passenger vehicles, it is essential to focus not only on safety but also on passenger comfort which is often overlooked in the design process. Integrating this in the design cycle requires a thorough understanding of the relation between objective metrics and the subjective passenger response. This paper introduces a novel multimodal measurement platform for efficient measurement of objective metrics and subjective comfort in a representative AD setting. The platform, built on a commercially available electric vehicle, contains sensors to concurrently capture data on vehicle dynamics, environmental conditions, and passenger physiological responses. An automated data processing pipeline has been developed to compute and visualize metrics related to both vehicle performance and passenger comfort. The platform has been utilized in a proving ground jury test, with preliminary qualitative analyses identifying potential comfort-related indicators, such as Time-to-Collision and Galvanic Skin Response. The platform and its processing pipeline will be the basis for further investigation into objective-subjective comfort correlation and prediction in the future.

Keywords: Autonomous Vehicles, Human Passenger Comfort, Physiological Measurement, Vehicle Dynamics, Sensor Fusion

DOI: 10.54941/ahfe1005852