9 papers
Zero-Shot MARL Benchmark in the Cyber-Physical Mobility Lab
Julius Beerwerth, Jianye Xu, Simon Schäfer +2
We present a reproducible benchmark for evaluating sim-to-real transfer of Multi-Agent Reinforcement Learning (MARL) policies for Connected and Automated Vehicles (CAVs). The platf…
Beyond Safety Filtering: Control Barrier Function-Informed Reinforcement Learning for Connected and Automated Vehicles
Jianye Xu, Bassam Alrifaee
Reinforcement Learning (RL) uses rewards to guide learning, yet reward design is typically hand-crafted using heuristics that can be difficult to tune. We propose a Control Barrier…
A Real-Time Control Barrier Function-Based Safety Filter for Motion Planning with Arbitrary Road Boundary Constraints
Jianye Xu, Chang Che, Bassam Alrifaee
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…
Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms: Challenges and a Roadmap
Jianye Xu, Johannes Betz, Armin Mokhtarian +11
This article proposes a roadmap to address the current challenges in small-scale testbeds for Connected and Automated Vehicles (CAVs) and robot swarms. The roadmap is a joint effor…
TTCBF: A Truncated Taylor Control Barrier Function for High-Order Safety Constraints
Jianye Xu, Bassam Alrifaee
Control Barrier Functions (CBFs) enforce safety by rendering a prescribed safe set forward invariant. However, standard CBFs are limited to safety constraints with relative degree…
A Learning-Based Control Barrier Function for Car-Like Robots: Toward Less Conservative Collision Avoidance
Jianye Xu, Bassam Alrifaee
We propose a learning-based Control Barrier Function (CBF) to reduce conservatism in collision avoidance for car-like robots. Traditional CBFs often use the Euclidean distance betw…