Multiple Agents Dispatch via Batch Synchronous Actor Critic in Autonomous Mobility on Demand Systems

Jiyao Li, Vicki Allan

2024

Abstract

Autonomous Mobility on Demand (AMoD) systems are a promising area in the emerging field of intelligent transportation systems. In this paper, we focus on the problem of how to dispatch a fleet of autonomous vehicles (AVs) within a city while balancing supply and demand. We first formulate the problem as a Markov Decision Process (MDP) of which the goal is to maximize the accumulated average reward, then propose the Multiagent Reinforcement Learning (MARL) framework. The Temporal-Spatial Dispatching Network (TSD-Net) that combines both policy and value network learns representation features facilitating spatial information with its temporal signals. The Batch Synchronous Actor Critic (BS-AC) samples experiences from the Rollout Buffer with replacement and trains parameters of the TSD-Net. Based on the state value from the TSD-Net, the Priority Destination Sampling Assignment (PDSA) algorithm defines orders’ priority by their destinations. Popular destinations are preferred as it is easier for agents to find future work in a popular location. Finally, with the real-world city scale dataset from Chicago, we compare our approach to several competing baselines. The results show that our method is able to outperform other baseline methods with respect to effectiveness, scalability, and robustness.

Paper Citation

in Harvard Style

Li J. and Allan V. (2024). Multiple Agents Dispatch via Batch Synchronous Actor Critic in Autonomous Mobility on Demand Systems. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 198-209. DOI: 10.5220/0012351700003636

in Bibtex Style

@conference{icaart24,
author={Jiyao Li and Vicki Allan},
title={Multiple Agents Dispatch via Batch Synchronous Actor Critic in Autonomous Mobility on Demand Systems},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2024},
pages={198-209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012351700003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Multiple Agents Dispatch via Batch Synchronous Actor Critic in Autonomous Mobility on Demand Systems
SN - 978-989-758-680-4
AU - Li J.
AU - Allan V.
PY - 2024
SP - 198
EP - 209
DO - 10.5220/0012351700003636
PB - SciTePress