تقرير
A Comparative Study of Algorithms for Intelligent Traffic Signal Control
| العنوان: | A Comparative Study of Algorithms for Intelligent Traffic Signal Control |
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| المؤلفون: | Chaudhuri, Hrishit, Masti, Vibha, Veerendranath, Vishruth, Natarajan, S |
| المصدر: | Machine Learning and Autonomous Systems. Springer, Singapore, 2022. 271-287 |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Systems and Control, Computer Science - Machine Learning, G.3, I.2.11 |
| الوصف: | In this paper, methods have been explored to effectively optimise traffic signal control to minimise waiting times and queue lengths, thereby increasing traffic flow. The traffic intersection was first defined as a Markov Decision Process, and a state representation, actions and rewards were chosen. Simulation of Urban MObility (SUMO) was used to simulate an intersection and then compare a Round Robin Scheduler, a Feedback Control mechanism and two Reinforcement Learning techniques - Deep Q Network (DQN) and Advantage Actor-Critic (A2C), as the policy for the traffic signal in the simulation under different scenarios. Finally, the methods were tested on a simulation of a real-world intersection in Bengaluru, India. Comment: 15 pages, 18 figures, ICMLAS 2021 Conference |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1007/978-981-16-7996-4_19 |
| URL الوصول: | http://arxiv.org/abs/2109.00937 |
| رقم الأكسشن: | edsarx.2109.00937 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1007/978-981-16-7996-4_19 |
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