2021/12/29 by Fang‐Chieh Chou, Chou, Fang-Chieh, Marsalis Gibson +7
Engineering · #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #FOS: Electrical engineering #Multiagent Systems (cs.MA) #Robotics (cs.RO) #Systems and Control (eess.SY) #Traffic and Road Safety #Traffic control and management #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2112.14345
openalex publication_date 2021/12/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm, which is a controller designed for dampening stop- and-go traffic waves. With more than 1100 miles of driving data collected by our physical platform, we validate our analysis results by comparing it to human driving behaviors. The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration. To expand upon previous analysis, reachability analysis is used to investigate the safety at the speeds it was originally tested and also at higher speeds. Two formulations of safety analysis with different criteria are shown: distance-based and time headway-based. The FollowerStopper is considered safe with distance-based criterion. However, simulation results demonstrate that the FollowerStopper is not representative of human drivers - it follows too closely behind vehicles, specifically at a distance human would deem as unsafe. On the other hand, under the time headway-based safety analysis, the FollowerStopper is not considered safe anymore. A modified FollowerStopper is proposed to satisfy time-based safety criterion. Simulation results of the proposed FollowerStopper shows that its response represents human driver behavior better.