Auction-Based Responsibility Allocation for Scalable Decentralized Safety Filters in Cooperative Multi-Agent Collision Avoidance

TL;DR

This paper introduces an auction-based responsibility allocation method for decentralized safety filters in multi-agent systems, improving scalability and efficiency while maintaining safety in collision avoidance tasks.

Contribution

It presents a novel auction-based scheme for distributing safety constraints among agents, addressing scalability and feasibility issues in decentralized control barrier functions.

Findings

Ensures safety coverage with reduced computational load.

Scales effectively to larger multi-agent networks.

Maintains safety and efficiency in simulations.

Abstract

This paper proposes a scalable decentralized safety filter for multi-agent systems based on high-order control barrier functions (HOCBFs) and auction-based responsibility allocation. While decentralized HOCBF formulations ensure pairwise safety under input bounds, they face feasibility and scalability challenges as the number of agents grows. Each agent must evaluate an increasing number of pairwise constraints, raising the risk of infeasibility and making it difficult to meet real-time requirements. To address this, we introduce an auction-based allocation scheme that distributes constraint enforcement asymmetrically among neighbors based on local control effort estimates. The resulting directed responsibility graph guarantees full safety coverage while reducing redundant constraints and per-agent computational load. Simulation results confirm safe and efficient coordination across a range of network sizes and interaction densities.