2023/10/01 by Anni Li, Li, Anni, Christos G. Cassandras +3 · 1 citation
Engineering · Psychology · #Autonomous Vehicle Technology and Safety #FOS: Electrical engineering #Human-Automation Interaction and Safety #Systems and Control (eess.SY) #Traffic control and management #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2310.00534
openalex publication_date 2023/10/01 · openalex created_date 2023/10/04 · openalex updated_date 2026/07/28
This paper studies safe driving interactions between Human-Driven Vehicles (HDVs) and Connected and Automated Vehicles (CAVs) in mixed traffic where the dynamics and control policies of HDVs are unknown and hard to predict. In order to address this challenge, we employ event-triggered Control Barrier Functions (CBFs) to estimate the HDV model online, construct data-driven and state-feedback safety controllers, and transform constrained optimal control problems for CAVs into a sequence of event-triggered quadratic programs. We show that we can ensure collision-free between HDVs and CAVs and demonstrate the robustness and flexibility of our framework on different types of human drivers in lane-changing scenarios while guaranteeing safety with human-in-the-loop interactions.