Towards a Very Large Scale Traffic Simulator for Multi-Agent Reinforcement Learning Testbeds

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Smart traffic control and management become an emerging application for Deep Reinforcement Learning (DRL) to solve traffic congestion problems in urban networks. Different traffic control and management policies can be tested on the traffic simulation. Current DRL-based studies are mainly supported by the microscopic simulation software (e.g., SUMO11https://www.eclipse.org/sumo/), while it is not suitable for city-wide control due to the computational burden and gridlock effect. To the best of our knowledge, there is a lack of studies on the large-scale traffic simulator for D RL testbeds. In view of this, we propose a meso-macro traffic simulator for very large-scale DRL scenarios. The proposed simulator integrates meso scopic and macroscopic traffic simulation models to improve efficiency and eliminate gridlocks. The meso scopic link model simulates flow dynamics on roads, and the macroscopic Bathtub model depicts vehicle movement in regions. Moreover, both types of models can be hybridized to accommodate various DRL tasks. The result shows that the developed simulator only takes 46 seconds to finish a 24-hour simulation in a very large city with 2.2 million vehicles, which is much faster than SUMO. In the future, the developed meso-macro traffic simulator could serve as a new environment for very large-scale DRL problems.

Original languageEnglish
Title of host publication2022 IEEE 25th International Conference on Intelligent Transportation Systems, ITSC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages363-368
Number of pages6
ISBN (Electronic)9781665468800
DOIs
Publication statusPublished - 2022
Event25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022 - Macau, China
Duration: 8 Oct 202212 Oct 2022

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2022-October

Conference

Conference25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022
Country/TerritoryChina
CityMacau
Period8/10/2212/10/22

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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