Robust Safety for Mixed-Autonomy Traffic with Delays and Disturbances

6 Oct 2023  ·  Chenguang Zhao, Huan Yu ·

Various control strategies and field experiments have been designed for connected and automated vehicles (CAVs) to stabilize mixed traffic that contains both CAVs and Human-driven Vehicles (HVs). The effect of these stabilizing CAV control strategies on traffic safety is still under investigation. In an effort to prioritize safety over stability, a safety-critical filter via control barrier functions (CBFs) can be designed by modifying the stabilizing nominal control input in a minimal fashion and imparting collision-free driving behaviors for CAVs and HVs. However, such formal safety guarantees can be violated if there are delays in the actuation and communication channels of the CAV. Considering both actuator and sensor delays, and disturbances, we propose robust safety-critical traffic control (RSTC) design to ensure ``robust safety'' of the mixed traffic. While predictor-based CBF has been developed to compensate for the actuator delay, uncertain speed disturbances from the head vehicle cause prediction error and require novel robust CBF design. Besides, safety-critical control with sensor delay also remains an open question. In RSTC, a state predictor with bounded error is designed, and robust CBF constraints are constructed to guarantee safety under actuator delay and disturbances. When there is a sensor delay, a state observer is designed and integrated with a predictor-based CBF to ensure robust safety. Numerical simulations demonstrate that the proposed RSTC avoids rear-end collisions for two unsafe traffic scenarios in the presence of actuator, sensor delays and disturbances.

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