Rule-Based Safety-Critical Control Design using Control Barrier Functions with Application to Autonomous Lane Change
Abstract
This paper develops a new control design for guaranteeing a vehicle's safety during lane change maneuvers in a complex traffic environment. The proposed method uses a finite state machine (FSM), where a quadratic program based optimization problem using control Lyapunov functions and control barrier functions (CLF-CBF-QP) is used to calculate the system's optimal inputs via rule-based control strategies. The FSM can make switches between different states automatically according to the command of driver and traffic environment, which makes the ego vehicle find a safe opportunity to do a collision-free lane change maneuver. By using a convex quadratic program, the controller can guarantee the system's safety at a high update frequency. A set of pre-designed typical lane change scenarios as well as randomly generated driving scenarios are simulated to show the performance of our controller.
Cite
@article{arxiv.2103.12382,
title = {Rule-Based Safety-Critical Control Design using Control Barrier Functions with Application to Autonomous Lane Change},
author = {Suiyi He and Jun Zeng and Bike Zhang and Koushil Sreenath},
journal= {arXiv preprint arXiv:2103.12382},
year = {2021}
}
Comments
Accepted to ACC 2021