A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment
The self-adaptive traffic signal control system serves as an effective measure for relieving urban traffic congestion. The system is capable of adjusting the signal timing parameters in real time according to the seasonal changes and short-term fluctuation of traffic demand, resulting in improvement...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/1096123 |
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| _version_ | 1832563329781989376 |
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| author | Yizhe Wang Xiaoguang Yang Hailun Liang Yangdong Liu |
| author_facet | Yizhe Wang Xiaoguang Yang Hailun Liang Yangdong Liu |
| author_sort | Yizhe Wang |
| collection | DOAJ |
| description | The self-adaptive traffic signal control system serves as an effective measure for relieving urban traffic congestion. The system is capable of adjusting the signal timing parameters in real time according to the seasonal changes and short-term fluctuation of traffic demand, resulting in improvement of the efficiency of traffic operation on urban road networks. The development of information technologies on computing science, autonomous driving, vehicle-to-vehicle, and mobile Internet has created a sufficient abundance of acquisition means for traffic data. Great improvements for data acquisition include the increase of available amount of holographic data, available data types, and accuracy. The article investigates the development of commonly used self-adaptive signal control systems in the world, their technical characteristics, the current research status of self-adaptive control methods, and the signal control methods for heterogeneous traffic flow composed of connected vehicles and autonomous vehicles. Finally, the article concluded that signal control based on multiagent reinforcement learning is a kind of closed-loop feedback adaptive control method, which outperforms many counterparts in terms of real-time characteristic, accuracy, and self-learning and therefore will be an important research focus of control method in future due to the property of “model-free” and “self-learning” that well accommodates the abundance of traffic information data. Besides, it will also provide an entry point and technical support for the development of Vehicle-to-X systems, Internet of vehicles, and autonomous driving industries. Therefore, the related achievements of the adaptive control system for the future traffic environment have extremely broad application prospects. |
| format | Article |
| id | doaj-art-f840e95bb4354de9ab04a9f292e771a1 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-f840e95bb4354de9ab04a9f292e771a12025-02-03T01:20:29ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/10961231096123A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic EnvironmentYizhe Wang0Xiaoguang Yang1Hailun Liang2Yangdong Liu3Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, ChinaThe self-adaptive traffic signal control system serves as an effective measure for relieving urban traffic congestion. The system is capable of adjusting the signal timing parameters in real time according to the seasonal changes and short-term fluctuation of traffic demand, resulting in improvement of the efficiency of traffic operation on urban road networks. The development of information technologies on computing science, autonomous driving, vehicle-to-vehicle, and mobile Internet has created a sufficient abundance of acquisition means for traffic data. Great improvements for data acquisition include the increase of available amount of holographic data, available data types, and accuracy. The article investigates the development of commonly used self-adaptive signal control systems in the world, their technical characteristics, the current research status of self-adaptive control methods, and the signal control methods for heterogeneous traffic flow composed of connected vehicles and autonomous vehicles. Finally, the article concluded that signal control based on multiagent reinforcement learning is a kind of closed-loop feedback adaptive control method, which outperforms many counterparts in terms of real-time characteristic, accuracy, and self-learning and therefore will be an important research focus of control method in future due to the property of “model-free” and “self-learning” that well accommodates the abundance of traffic information data. Besides, it will also provide an entry point and technical support for the development of Vehicle-to-X systems, Internet of vehicles, and autonomous driving industries. Therefore, the related achievements of the adaptive control system for the future traffic environment have extremely broad application prospects.http://dx.doi.org/10.1155/2018/1096123 |
| spellingShingle | Yizhe Wang Xiaoguang Yang Hailun Liang Yangdong Liu A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment Journal of Advanced Transportation |
| title | A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment |
| title_full | A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment |
| title_fullStr | A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment |
| title_full_unstemmed | A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment |
| title_short | A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment |
| title_sort | review of the self adaptive traffic signal control system based on future traffic environment |
| url | http://dx.doi.org/10.1155/2018/1096123 |
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