Research on traffic signal cycle optimization based on Webster algorithm
DOI:
https://doi.org/10.54097/nwddhg31Keywords:
Cluster Analysis, Webster Method, Signal Timing.Abstract
This study by combining data cleaning, clustering analysis and signal timing method, Webster to famous scenic town traffic control provides a scientific and efficient solution. By removing the missing license plate numbers and abnormal data in the open source data set, the processed data were visualized and analyzed. The cluster analysis was used to divide the peak period of traffic flow, the statistics of the traffic flow period data, the Webster method was used to optimize the timing of traffic lights, and the service level model was established to analyze the results. It was found that it could effectively improve the traffic efficiency. Ease traffic congestion. This research is not only of great significance in theory, but also has application value in actual traffic management, showing its innovation and practical value. The future research of algorithms and to further explore the more advanced technology, to achieve more accurate and efficient traffic flow control.
Downloads
References
[1] Yang Huanhong, Chai Lei, Huang Wentao, et al. Collaborative optimization of dual source tram and electric bus considering road traffic information [J]. Power System Automation, 2024, 48 (17): 77-87.
[2] Wang Shuang, Chen Weiwei, Liu Menglong, et al. Optimization of Road Intersection Organization and Signal Control in Small and Medium sized Towns Based on Webster's Principle [J]. Engineering Technology Research, 2022, 7 (19): 7-9.
[3] Bo Wu, Gong Xu, Luo Lvtian, et al. Optimization effect of Webster's algorithm on queue delay under different traffic flows [J]. Transport Manager World, 2024, (01): 164-166.
[4] Ikotun A M, Ezugwu A E, Abualigah L, et al. K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data [J]. Information Sciences, 2023, 622: 178-210.
[5] Sun Jigui, Liu Jie, Zhao Lianyu. Research on Clustering Algorithm [J]. Journal of Software, 2008, (01): 48-61.
[6] Zhu Lianjiang, Ma Bingxian, Zhao Xuequan. Cluster validity analysis based on contour coefficient [J]. Computer Applications, 2010, 30 (S2): 139-141+198.
[7] Jain a K, Murty M N, Flynn P J. Data clustering: a review [J]. ACM computing surveys (CSUR), 1999, 31(3): 264-323.
[8] Manochandar S, Punniyamoorthy M, Jeyachitra R K. Development of new seed with modified validity measures for k-means clustering [J]. Computers & Industrial Engineering, 2020, 141: 106290.
[9] Ba Tianxing, Meng Ziyue, Yu Shize. Application research on intersection timing optimization method based on Webster's method [J]. People's Public Transport, 2024, (12): 49-51.
[10] Wu Luxiang, Guan Xingquan, Yan Lei, et al. Research on Intersection Signal Timing Optimization Based on VISSIM Simulation [J]. Logistics Engineering and Management, 2021, 43 (12): 35-38.
[11] Huang Wenman. Signal optimization of typical cross shaped intersections based on Synchro system [J]. Transportation and Communications, 2024, 37 (S1): 101-104+112.
[12] Hu Mingwei, Zhai Suyun, Duan Huabo, et al. Comparative Analysis of Low Emission Zones in Europe [J]. Journal of Shenzhen University (Science and Engineering Edition), 2017, 34 (03): 229-237.
Downloads
Published
Conference Proceedings Volume
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.