Control-sharing Control Barrier Functions for Intersection Automation under Input Constraints

Abstract

This contribution introduces a centralized input constrained optimal control framework based on multiple control barrier functions (CBFs) to coordinate connected and automated agents at intersections. For collision avoidance, we propose a novel CBF which is safe by construction. The given control scheme provides provable guarantees that collision avoidance CBFs and CBFs to constrain the agents' velocity are jointly feasible (referred to as control-sharing property) subject to input constraints. A simulation study finally provides evidence that the proposed control scheme is safe.

A Barrier-Certified Optimal Coordination Framework for Connected and Automated Vehicles

“…More recently, there have been a series of papers initially proposed by Xiao et al [20], [21] on using CBFs in the coordination of CAVs [20]- [24]. Xiao et al [21], provided a joint CBF and CLF approach to respond to inevitable perturbation and noise in a highway merging problem.…”

“…Although several studies on coordination of CAVs at different traffic scenarios using CBFs have been reported in the literature, the approach reported in this paper advances the state of the art in the following ways. First, in contrast to other efforts which attempt to address satisfaction of all the constraints in the system through CBFs [21]- [24], in this paper, the motion planning module yields an optimal unconstrained trajectory which guarantees that state, control, and safety constraints are satisfied, while barrier-certificate module only intervenes if the deviations from the nominal optimal trajectory lead to violating the constraints. Second, in several research efforts using CBFs, the lateral safety is handled through imposing a FIFO queuing policy [20]- [23].…”