Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning

Ujwal Padam Tewari; Vishal Bidawatka; Varsha Raveendran; Vinay Sudhakaran; Shreedhar Kodate Shreeshail; Jayanth Prakash Kulkarni

arXiv · 1912.03851

Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning

Ujwal Padam Tewari·Vishal Bidawatka·Varsha Raveendran·Vinay Sudhakaran·Shreedhar Kodate Shreeshail·Jayanth Prakash Kulkarni

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Abstract

We use Asynchronous Advantage Actor Critic (A3C) for implementing an AI agent in the controllers that optimize flow of traffic across a single intersection and then extend it to multiple intersections by considering a multi-agent setting. We explore three different methodologies to address the multi-agent problem - (1) use of asynchronous property of A3C to control multiple intersections using a single agent (2) utilise self/competitive play among independent agents across multiple intersections and (3) ingest a global reward function among agents to introduce cooperative behavior between intersections. We observe that (1) & (2) leads to a reduction in traffic congestion. Additionally the use of (3) with (1) & (2) led to a further reduction in congestion.

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Ujwal Padam Tewari, Vishal Bidawatka, Varsha Raveendran, Vinay Sudhakaran, Shreedhar Kodate Shreeshail, Jayanth Prakash Kulkarni. 2020-06-28. Intelligent Coordination among Multiple Traffic Intersections Using Multi-Agent Reinforcement Learning. https://arxiv.org/abs/1912.03851

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