Human-centric validation framework for monitoring systems embedded in conditionally automated vehicles

Abstract

The advancement of automated driving technology has led to the enhanced performance of various subsystems integrated into automated vehicles, with their design conforming to international standards and regulatory guidelines. However, the corresponding performance evaluations often overlook human perspectives, such as those of drivers or passengers, potentially resulting in a lack of system safety or customer satisfaction. Therefore, these factors must be considered during testing to ensure the secure and satisfactory operation of automated vehicles. To evaluate the performance of systems embedded in automated vehicles from a human perspective, this paper introduces a framework based on the system-theoretic process analysis, which is a systems approach to analyze hazards attributable to human factors. The Driver Availability Recognition System in the SAE Level 3 automated vehicle was selected as a verification system, and a full-scale driving simulator was used to create the experimental environment. Forty volunteers participated in the performance verification experiment, and data obtained from the human-in-the-loop experiment were incorporated into the proposed framework. The results demonstrated that the framework can ensure effective performance evaluation from a human perspective and suggest safety requirements. The development and application of the proposed framework are anticipated to facilitate the successful rollout of automated vehicles.