English

A Hybrid Framework for Multi-Vehicle Collision Avoidance

Optimization and Control 2017-03-23 v1

Abstract

With the recent surge of interest in UAVs for civilian services, the importance of developing tractable multi-agent analysis techniques that provide safety and performance guarantees have drastically increased. Hamilton-Jacobi (HJ) reachability has successfully provided these guarantees to small-scale systems and is flexible in terms of system dynamics. However, the exponential complexity scaling of HJ reachability with respect to system dimension prevents its direct application to larger-scale problems where the number of vehicles is greater than two. In this paper, we propose a collision avoidance algorithm using a hybrid framework for N+1 vehicles through higher-level control logic given any N-vehicle collision avoidance algorithm. Our algorithm conservatively approximates a guaranteed-safe region in the joint state space of the N+1 vehicles and produces a safety-preserving controller. In addition, our algorithm does not incur significant additional computation cost. We demonstrate our proposed method in simulation.

Cite

@article{arxiv.1703.07375,
  title  = {A Hybrid Framework for Multi-Vehicle Collision Avoidance},
  author = {Aparna Dhinakaran and Mo Chen and Glen Chou and Jennifer C. Shih and Claire J. Tomlin},
  journal= {arXiv preprint arXiv:1703.07375},
  year   = {2017}
}

Comments

Submitted to IEEE Conference on Decision and Control, 2017

R2 v1 2026-06-22T18:53:01.095Z