2021/03/08 by Chao Huang, Chen Lv, Huang, Chao +7
Computer Science · Engineering · Psychology · #Autonomous Vehicle Technology and Safety #FOS: Electrical engineering #Human-Automation Interaction and Safety #Systems and Control (eess.SY) #Traffic control and management #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2103.04563
arxiv created 2021/03/08 · openalex publication_date 2021/03/08 · arxiv updated 2021/03/09 · openalex created_date 2021/03/15 · openalex updated_date 2026/07/28
In this paper, a human-machine adaptive shared control method is proposed for automated vehicles (AVs) under automation performance degradation. First, a novel risk assessment module is proposed to monitor driving behavior and evaluate automation performance degradation for AVs. Then, an adaptive control authority allocation module is developed. In the event of any performance degradation detection, the allocated control authority of the automation system is decreased based on the assessed risk to reduce the potential risk of vehicle motion. Consequently, the control authority allocated to the human driver is adaptively increased and thus requires more driver engagement in the control loop to compensate for the automation degradation and ensure AV safety. Experimental validation is conducted under different driving scenarios. The testing results show that the proposed approach is able to effectively compensate for the performance degradation of vehicle automation through the human-machine adaptive shared control, ensuring the safety of automated driving