A Survey on Traffic Signal Control Methods

2019-04-17 · Hua Wei, Guanjie Zheng, Vikash Gayah, Zhenhui Li

Traffic signal control is an important and challenging real-world problem, which aims to minimize the travel time of vehicles by coordinating their movements at the road intersections. Current traffic signal control systems in use still rely heavily on oversimplified information and rule-based methods, although we now have richer data, more computing power and advanced methods to drive the development of intelligent transportation. With the growing interest in intelligent transportation using machine learning methods like reinforcement learning, this survey covers the widely acknowledged transportation approaches and a comprehensive list of recent literature on reinforcement for traffic signal control. We hope this survey can foster interdisciplinary research on this important topic.

📄 PDF Abstract BibTeX arXiv:1904.08117

Code (0)

등록된 구현이 없습니다.

Tasks

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)SurveyTraffic Signal Control

Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey

2020-05-02 · Ammar Haydari, Yasin Yilmaz

Latest technological improvements increased the quality of transportation. New data-driven approaches bring out a new research direction for all control-based systems, e.g., in transportation, robotics, IoT and power sys…

Autonomous Driving Deep Reinforcement Learning reinforcement-learning Reinforcement Learning+3

SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras

2024-08-18 · Tiejin Chen, Prithvi Shirke, Bharatesh Chakravarthi, Arpitsinh Vaghela 외

This paper introduces SynTraC, the first public image-based traffic signal control dataset, aimed at bridging the gap between simulated environments and real-world traffic management challenges. Unlike traditional datase…

Management Traffic Signal Control

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

2026-07-29 · Truong Giang Vu, Li Yang, Richard W. Pazzi arxiv

Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ride-hailing dispatch. Deep learning models, including graph convoluti…

Neural Architecture Search Traffic Prediction

Real-Time Traffic Signal Control for Modern Roundabouts by Using Particle Swarm Optimization-Based Fuzzy Controller

2014-08-04 · Yue-Jiao Gong, Jun Zhang

Due to that the existing traffic facilities can hardly be extended, developing traffic signal control methods is the most important way to improve the traffic efficiency of modern roundabouts. This paper proposes a novel…

Traffic Signal Control

MoveLight: Enhancing Traffic Signal Control through Movement-Centric Deep Reinforcement Learning

2024-07-24 · Junqi Shao, Chenhao Zheng, Yuxuan Chen, YuCheng Huang 외

This paper introduces MoveLight, a novel traffic signal control system that enhances urban traffic management through movement-centric deep reinforcement learning. By leveraging detailed real-time data and advanced machi…

Deep Reinforcement Learning Management reinforcement-learning Reinforcement Learning+1