Optimization Model and Method of Urban Road Traffic Signal Control under Rainfall Environment

doi:10.16182/j.issn1004731x.joss.19-0675

Abstract

Abstract: The efficiency of urban road traffic operation fell obviously during a rain, and the existing road traffic signal control has not yet established a relevant signal optimization scheme. Considering the traffic operation scenario under the influence of rainfall and road water, an urban road traffic cyber physical systems is designed, a framework of urban road traffic control based on cyber physical systems is built, an optimization model of traffic signal control is established, and further more, the solution method of the model is designed by using BP neural network. Building a traffic simulation model of the example intersection, comparing the delay time and other indicators under the three schemes, the analysis results proved the effectiveness of this method in improving the traffic operation efficiency of the intersection under the rainfall scenario.

Key words: rainfall scenario, traffic signal control, cyber physical system, BP neural network

CLC Number:

U491.4

Tang Shaohu, Zhou Jin, Shang Chunlin, Zheng Guorong. Optimization Model and Method of Urban Road Traffic Signal Control under Rainfall Environment[J]. Journal of System Simulation, 2020, 32(2): 149-156.

References

[1] Transportation Research Board.Highway capacity manual[M]. Washington. DC: National Research Council, 2000.
[2] Bernardin L, Associates. Anchorage signal system upgrade-final report[R]. Municipality of Anchorage, Alaska, 1995.
[3] Martin P, Perrin J, Hansen B, et al.Inclement Weather Signal Timings[R]. Fiber Optics, 2000.
[4] Perrin H, Martin P, Hansen B.Modifying Signal Timing During Inclement Weather[J]. Transportation Research Record: Journal of the Transportation Research Board (S0361-1981), 2001, 1748: 66-71.
[5] Mohan M, Chandra S.Queue clearance rate method for estimating passenger car equivalents at signalized intersections[J]. Journal of Traffic and Transportation Engineering (English Edition)(S2095-7564), 2017, 4(5): 487-495.
[6] 蒋贤才, 汪贝, 曾永松. 不良天气和路面环境对交通信号配时方案的影响[J]. 公路交通科技, 2014, 31(7): 135-142.
Jiang Xiancai, Wang Bei, Zeng Yongsong.Influence of Inclement Weather and Poor Road Condition on Traffic Signal Timing Scheme[J]. Journal of Highway and Transportation Research and Development, 2014, 31(7): 135-142.
[7] 胡明伟. 不良天气对交通信号配时的影响分析[J]. 交通运输研究, 2007(9): 156-160.
Hu Mingwei.Analysis on Adverse Weather on Traffic Signal Timing[J]. Transport Research, 2007 (9): 156-160.
[8] 李岩, 南斯睿, 马静, 等. 降雨天气单点交叉口交通信号控制优化方法[J]. 交通运输工程学报, 2018, 18(5): 189-198.
Li Yan, Nan Sirui, Ma Jing, et al.Optimization method for traffic signal control of isolated intersection under rainy weather[J]. Journal of Traffic and Transportation Engineering, 2018, 18(5): 189-198.
[9] 武丽佳. 不良天气下交叉口交通流特征及其单点信号控制策略[D]. 南京: 东南大学, 2018.
Wu Lijia.Traffic flow characteristic and signal control strategy of single intersection under adverse weather[D]. Ningjing: Southeast University, 2018.
[10] 温景容, 武穆清, 宿景芳. 信息物理融合系统[J]. 自动化学报, 2012, 38(4): 507-517.
Wen Jingrong, Wu Muqing, Su Jingfang.Cyber-physical System[J]. Acta Automatica Sinica, 2012, 38(4): 507-517.
[11] Rajkumar R R, Lee I, Sha L, et al.Cyber-Physical Systems: The Next Computing Revolution[C]// Proceedings of the 47th Design Automation Conference, DAC 2010. Anaheim, CA, USA. 2010.
[12] 乔国梁. 不利天气条件下城市路段交通流特征参数研究[D]. 北京: 北京工业大学, 2014.
Qiao Guoliang.Research on traffic flow characteristic parameters of urban road section in adverse weather conditions[D]. Beijing: Beijing University of Technology, 2014.
[13] 童波. 基于情景感知的CPS体系架构研究[D]. 青岛: 青岛科技大学, 2015.
Tong Bo.Research on architecture of CPS system based on context-aware[D]. Qingdao: Qingdao University of Science and Technology, 2015.
[14] 刘力力. 不利天气条件下城市交叉口交通流特征参数研究[D]. 北京: 北京工业大学, 2013.
Liu Lili.Research on traffic flow characteristic parameters of city intersection in adverse weather condition[D]. Beijing: Beijing University of Technology, 2013.
[15] 范一丁. 降雨内涝情景下城市路网脆弱性研究[D]. 哈尔滨: 哈尔滨工业大学, 2017.
Fan Yiding.Research on vulnerability of road network under urban waterlogging[D]. Harbin: Harbin Institute of Technology, 2017.
[16] 张起森, 张亚平. 道路通行能力分析[M]. 北京: 人民交通出版社, 2002.
Zhang Qisen, Zhang Yaping.Highway Capacity Analysis[M]. Beijing: China Communications Press, 2002.
[17] Rumelhart D E, Mcclelland J L.Parallel distributed processing: explorations in the microstructure of cognition[M]. Cambridge, Massachusetts: MIT Press, 1986.
[18] 唐少虎, 刘小明. 基于IAGSO 算法的VISSIM模型校正研究与实现[J]. 交通运输系统工程与信息, 2014, 14(5): 74-80.
Tang Shaohu, Liu Xiaoming.VISSIM Model Calibration Based on IAGSO Algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(5): 74-80.