Alleviating Traffic Congestion: Developing and Evaluating Novel Multi-Agent Reinforcement Learning Traffic Light Coordination Techniques
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2023-07-01
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Edition:Final Research Report
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Abstract:Traffic congestion costs American cities tens of billions of dollars per year, not to mention its negative impact on the environment or people’s mental health. Novel Markov game models and advanced reinforcement learning algorithms hold the promise of drastically alleviating congestion through dynamic coordination of traffic signals and adaptive techniques to dynamically re-route traffic. This project involves a collaboration with Econolite, a leading provider of traffic management systems.
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