Traffic control optimization strategy based on license plate recognition data
Traffic signal control is essential to the efficiency of the road network's operation. In recent years, more and more detailed detection data provide potential data support for traffic signal control, such as license plate recognition (LPR) data. This study aims to develop a traffic signal cont...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2023-02-01
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| Series: | Journal of Traffic and Transportation Engineering (English ed. Online) |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095756423000028 |
| _version_ | 1797893777802657792 |
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| author | Ruimin Li Shi Wang Pengpeng Jiao Shichao Lin |
| author_facet | Ruimin Li Shi Wang Pengpeng Jiao Shichao Lin |
| author_sort | Ruimin Li |
| collection | DOAJ |
| description | Traffic signal control is essential to the efficiency of the road network's operation. In recent years, more and more detailed detection data provide potential data support for traffic signal control, such as license plate recognition (LPR) data. This study aims to develop a traffic signal control optimization method based on model predictive control (MPC) and LPR data. The proposed framework of a closed-loop control system is described in detail. First, the control objectives and queue prediction model for signalized intersection are determined. Then, online optimization and feedback compensation are discussed and implemented. Calculations of the arrival rate at the downstream are based on the LPR data detected at the upstream intersection, and dynamic optimization method of the offset is proposed for a coordinated control. The model is validated using the LPR data of two consecutive intersections with a traffic simulation platform. Results demonstrate that the model can restrain extreme long queuing, improve intersection capacity, and reduce intersection average delay. The developed model promotes the system operating efficiency and shows the general advantage of real-time optimization, feedback, and control. The proposed framework can be potentially applied by local traffic management centers to improve the quality of traffic signal control. |
| first_indexed | 2024-04-10T06:59:30Z |
| format | Article |
| id | doaj.art-6ee823d2e05f48c8a8de52b7cb544358 |
| institution | Directory Open Access Journal |
| issn | 2095-7564 |
| language | English |
| last_indexed | 2024-04-10T06:59:30Z |
| publishDate | 2023-02-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Traffic and Transportation Engineering (English ed. Online) |
| spelling | doaj.art-6ee823d2e05f48c8a8de52b7cb5443582023-02-28T04:08:36ZengKeAi Communications Co., Ltd.Journal of Traffic and Transportation Engineering (English ed. Online)2095-75642023-02-011014557Traffic control optimization strategy based on license plate recognition dataRuimin Li0Shi Wang1Pengpeng Jiao2Shichao Lin3Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China; Corresponding author. Tel.: +86 10 62770985.Department of Civil Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USASchool of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, ChinaInstitute of Transportation Engineering, Tsinghua University, Beijing 100084, ChinaTraffic signal control is essential to the efficiency of the road network's operation. In recent years, more and more detailed detection data provide potential data support for traffic signal control, such as license plate recognition (LPR) data. This study aims to develop a traffic signal control optimization method based on model predictive control (MPC) and LPR data. The proposed framework of a closed-loop control system is described in detail. First, the control objectives and queue prediction model for signalized intersection are determined. Then, online optimization and feedback compensation are discussed and implemented. Calculations of the arrival rate at the downstream are based on the LPR data detected at the upstream intersection, and dynamic optimization method of the offset is proposed for a coordinated control. The model is validated using the LPR data of two consecutive intersections with a traffic simulation platform. Results demonstrate that the model can restrain extreme long queuing, improve intersection capacity, and reduce intersection average delay. The developed model promotes the system operating efficiency and shows the general advantage of real-time optimization, feedback, and control. The proposed framework can be potentially applied by local traffic management centers to improve the quality of traffic signal control.http://www.sciencedirect.com/science/article/pii/S2095756423000028Traffic controlModel predictive controlClosed-loop controlLicense plate recognition data |
| spellingShingle | Ruimin Li Shi Wang Pengpeng Jiao Shichao Lin Traffic control optimization strategy based on license plate recognition data Journal of Traffic and Transportation Engineering (English ed. Online) Traffic control Model predictive control Closed-loop control License plate recognition data |
| title | Traffic control optimization strategy based on license plate recognition data |
| title_full | Traffic control optimization strategy based on license plate recognition data |
| title_fullStr | Traffic control optimization strategy based on license plate recognition data |
| title_full_unstemmed | Traffic control optimization strategy based on license plate recognition data |
| title_short | Traffic control optimization strategy based on license plate recognition data |
| title_sort | traffic control optimization strategy based on license plate recognition data |
| topic | Traffic control Model predictive control Closed-loop control License plate recognition data |
| url | http://www.sciencedirect.com/science/article/pii/S2095756423000028 |
| work_keys_str_mv | AT ruiminli trafficcontroloptimizationstrategybasedonlicenseplaterecognitiondata AT shiwang trafficcontroloptimizationstrategybasedonlicenseplaterecognitiondata AT pengpengjiao trafficcontroloptimizationstrategybasedonlicenseplaterecognitiondata AT shichaolin trafficcontroloptimizationstrategybasedonlicenseplaterecognitiondata |