Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding (Extended Abstract)


  • Zhe Chen Monash University
  • Daniel Harabor Monash University
  • Jiaoyang Li Carnegie Mellon University
  • Peter J. Stuckey Monash University OPTIMA Australian Research Council ITTC, Melbourne, Australia



Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics that asks us to compute collision-free paths for a team of agents, all moving across a shared map. Existing scalable approaches struggle as the number of agents grows, as they typically plan free-flow optimal paths, which creates congestion. To tackle this issue, we propose a new approach for MAPF where agents are guided to their destination by following congestion-avoiding paths. Empirically, we report large improvements in overall throughput for lifelong MAPF while coordinating more than ten thousand agents.