Xu, Jianye (RWTH Aachen University), Che, Chang (RWTH Aachen University), Alrifaee, Bassam (University of the Bundeswehr Munich)

A Real-Time Control Barrier Function-Based Safety Filter for Motion Planning with Arbitrary Road Boundary Constraints

Scheduled for presentation during the Regular Session "S41a-Motion Planning, Trajectory Optimization, and Control for Autonomous Vehicles" (FR-LM-T41), Friday, November 21, 2025, 11:50−12:10, Broadbeach 1&2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

We present a real-time safety filter for motion planning, including those that are learning-based, using Control Barrier Functions (CBFs) to provide formal guarantees for collision avoidance with road boundaries. A key feature of our approach is its ability to directly incorporate road geometries of arbitrary shape that are represented as polylines without resorting to conservative overapproximations. We formulate the safety filter as a constrained optimization problem as a Quadratic Program (QP), which achieves safety by making minimal, necessary adjustments to the control actions issued by the nominal motion planner. We validate our safety filter through extensive numerical experiments across a variety of traffic scenarios featuring complex road boundaries. The results confirm its reliable safety and high computational efficiency (execution frequency up to 40 Hz). Code reproducing our experimental results and a video demonstration are available at github.com/bassamlab/SigmaRL.