A Coordinated Control Method of Traffic Signals for Recurrent Congested Network Locations
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摘要: 针对高峰期间常发拥堵点交通需求过大、周边关联交叉口交通负荷分布不均的问题, 研究了面向常发拥堵点的交通信号协调控制方法。通过对常发拥堵点的车流进行追踪与溯源, 根据交通量关联度确定信号协调控制范围, 然后基于路径的流量分担率与路段平均饱和度识别信号协调控制范围内的关键路径。基于宏观基本图理论, 考虑关键路径对路网运行状态的影响, 构建边界交叉口主动限流控制模型。同时, 利用元胞传输模型描述交叉口与路段的运行状态, 以关键路径通行能力最大化和进口道饱和度均衡化为信号控制优化目标, 建立均衡路网交通负荷的信号控制优化模型。以武汉市发展大道青年路交叉口以及关联交叉口为对象开展仿真实验, 结果表明: 虽然本文方法下的边界交叉口车均延误增加了6.8 s, 但常发拥堵点的车均延误降低了15.7 s; 关键路径的车均延误减少72.6 s, 平均排队长度减少26.1 m。并且, 路网整体的车均延误降低14.7%, 驶出车辆数增加26.6%, 验证了提出方法缓解常发拥堵点交通拥堵的有效性。Abstract: Traffic volume at recurrent congestion points is excessive, and the distribution of traffic load at associated intersections is unbalanced during peak hours. A coordinated control method of traffic signal for recurrent congestion points is proposed to solve the above problems. By tracking the traffic flow at the recurrent congestion point, the coordinated signal control area is determined according to a correlation of traffic volume. Then, the critical route of the coordinated signal control area is identified according to the traffic flow sharing rate and the average saturation of road sections. Based on the macroscopic fundamental diagram, an active perimeter control model considering the influences of critical routes on the state of road network is constructed. Meanwhile, a cell transmission model is used to describe the operating state of intersections and road sections. Maximum critical route capacity and equilibrium saturation of approaches are taken as the optimization objectives of signal control. A optimization model of signal control for balancing traffic load of road network is constructed. A simulation is carried out around the intersection of Wuhan Fazhan Avenue and Qingnian Road with its associated intersections. The results indicate that the average vehicle delay of boundary intersections increases by 6.8 s, but the average vehicle delay of the recurrent congestion point decreases by 15.7 s. The average vehicle delay decreases by 72.6 s, and queue length of the critical route decreases 26.1 m. Besides, the average vehicle delay of the road network is decreased by 14.7%, and the output traffic volume of the road network is increased by 26.6%.The simulation results verified the effectiveness of the proposed signal control method in alleviating traffic congestion at recurrent congestion points.
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表 1 外部道路输入流量
Table 1. Input volume of the external road
外部道路 流量/(veh/h) 外部道路 流量/(veh/h) R1 2 109 R10 1 998 R2 1 702 R11 1 887 R3 1 907 R12 2 204 R4 1 675 R13 1 731 R5 2 142 R14 2 372 R6 2 263 R15 2 100 R7 1 504 R16 1 794 R8 2 134 R17 1 816 R9 1 649 表 2 交通运行评价指标对比
Table 2. Comparison of traffic-operation evaluation indices
交通运行评价指标 控制方法 优化效果/% 干道协调 本文方法 路网车辆平均延误/(s/veh) 276.5 235.9 -14.7 驶离路网的车辆数/veh 17 262 21 854 26.6 关键路径车辆平均延误/(s/veh) 357.7 285.1 -20.3 关键路径平均排队长度/m 151.8 125.7 -17.2 常发拥堵点的车辆平均延误/(s/veh) 83.2 67.5 -18.9 边界交叉口车辆平均延误/(s/veh) 29.4 36.2 23.1 -
[1] 俞灏, 刘攀, 柏璐, 等. 考虑交通事件影响的动态交通信号控制策略[J]. 交通运输工程学报, 2019, 19(6): 182-190. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC201906019.htmYU Hao, LIU Pan, BAI Lu, et al. Dynamic traffic signal control strategies considering traffic incidents[J]. Journal of Traffic and Transportation Engineering, 2019, 19(6): 182-190. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC201906019.htm [2] LERTWORAWANICH P, KUWAHARA M, MISKA M. A new multiobjective signal optimization for oversaturated networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4): 967-976. doi: 10.1109/TITS.2011.2125957 [3] ABOUDOLAS K, PAPAGEORGIOU M, KOSMATOPOULOS E. Store-and-forward based methods for the signal control problem in large-scale congested urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2009, 17(2): 163-174. doi: 10.1016/j.trc.2008.10.002 [4] ABOUDOLAS K, PAPAGEORGIOU M, KOUVELAS A, et al. A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2010, 18(5): 680-694. doi: 10.1016/j.trc.2009.06.003 [5] 罗一尧. 城市交通路网拥堵控制研究[D]. 上海: 上海交通大学, 2016.LUO Yiyao. Research on control of urban traffic network congestion[D]. Shanghai: Shanghai Jiaotong University, 2016. (in Chinese) [6] 刘树青. 城市交通拥堵主动防控与快速疏导控制方法研究[D]. 广州: 华南理工大学, 2017.LIU Shuqing. Study on active prevention and fast evacuation control of urban traffic congestion[D]. Guangzhou: South China University of Technology, 2017. (in Chinese) [7] 李瑞敏. 过饱和交叉口交通信号控制研究现状与展望[J]. 交通运输工程学报, 2013, 13(6): 119-126. doi: 10.3969/j.issn.1671-1637.2013.06.017LI Ruimin. Study status and prospect of traffic signal control for over-saturated intersection[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6): 119-126. (in Chinese) doi: 10.3969/j.issn.1671-1637.2013.06.017 [8] XIN Wuping, CHANG J, MUTHUSWAMY S, et al. Multiregime adaptive signal control for congested urban roadway networks[J]. Transportation Research Record: Journal of the Transportation Research Board, 2013, 2366(1): 44-52. doi: 10.3141/2356-06 [9] 吴佳浩. 过饱和交通状态下城市交通信号优化控制研究[D]. 杭州: 浙江工业大学, 2017.WU Jiahao. Research on the optimal control of urban traffic signal under oversaturated traffic conditions[D]. Hangzhou: Zhejiang University of Technology, 2017. (in Chinese) [10] WU Na, LI Dewei, XI Yugeng. Distributed weighted balanced control of traffic signals for urban traffic congestion[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(10): 3710-3720. doi: 10.1109/TITS.2018.2878001 [11] 张梁. 基于短时交通流预测的城市常发性拥堵区域交通控制研究[D]. 青岛: 山东科技大学, 2017.ZHANG Liang. Urban traffic congestion control based on short term traffic flow forecasting[D]. Qingdao: Shandong University of Science and Technology, 2017. (in Chinese) [12] 郜轶敏, 张存保, 韦媛媛, 等. 考虑可变导向车道的干线交叉口协调控制方法[J]. 交通信息与安全, 2019, 37(5): 54-62. doi: 10.3963/j.issn.1674-4861.2019.05.008GAO Yimin, ZHANG Cunbao, Wei Yuanyuan, et al. A method of coordinated control for arterial intersections with variable lanes[J]. Journal of Transport Information and Safety, 2019, 37(5): 54-62. (in Chinese) doi: 10.3963/j.issn.1674-4861.2019.05.008 [13] 李岩, 过秀成, 杨洁, 等. 过饱和状态交叉口群信号控制机理及实施框架[J]. 交通运输系统工程与信息, 2011, 11(4): 28-34. doi: 10.3969/j.issn.1009-6744.2011.04.005LI Yan, GUO Xiucheng, YANG Jie, et al. Mechanism analysis and implementation framework for traffic signal control of over-saturated intersection group[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(4): 28-34. (in Chinese) doi: 10.3969/j.issn.1009-6744.2011.04.005 [14] 王辉. 交叉口群过饱和控制策略研究[D]. 武汉: 华中科技大学, 2014.WANG Hui. Research on the control strategy for over-saturated intersection group[D]. Wuhan: Huazhong University of Science and Technology, 2014. (in Chinese) [15] 王福建, 龚成宇, 马东方, 等. 采用交通出行量数据的多点联动瓶颈控制方法[J]. 浙江大学学报(工学版), 2017, 51(2): 273-278. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC201702007.htmWANG Fujian, GONG Chengyu, MA Dongfang, et al. Signal coordination control for traffic bottleneck using OD data[J]. Journal of Zhejiang University(Engineering Science), 2017, 51(2): 273-278. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC201702007.htm [16] LI Yishun, XU Jianmin, SHEN Lvou. A perimeter control strategy for oversaturated network preventing queue spillback[J]. Procedia-Social and Behavioral Sciences, 2012(43): 418-427. http://www.onacademic.com/detail/journal_1000035082653010_e0e6.html [17] KEYVAN-EKBATANI M, PAPAGEORGIOU M, PAPAMICHAIL I. Urban congestion gating control based on reduced operational network fundamental diagrams[J]. Tramsportation Research Part C: Emerging Technologies, 2013(33): 74-87. [18] KEYVAN-EKBATANI M, YILDIRIMOGLU M, GEROLIMINIS N, et al. Multiple concentric gating traffic control in large-scale urban networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4): 2141-2154. doi: 10.1109/TITS.2015.2399303 [19] 丁恒, 郑小燕, 张雨, 等. 宏观交通网络拥堵区边界最优控制[J]. 中国公路学报, 2017, 30(1): 111-120. doi: 10.3969/j.issn.1001-7372.2017.01.014DING Heng, ZHENG Xiaoyan, ZHANG Yu, et al. Optimal control for traffic congested area boundary in macroscopic trffic network[J]. China Journal of Highway and Transport, 2017, 30(1): 111-120. (in Chinese) doi: 10.3969/j.issn.1001-7372.2017.01.014 [20] Ji-Yang Beibei, MO Chao, MA Wanjing, et al. Feedback gating control for network based on macroscopic fundamental diagram[J]. Mathematical Problems in Engineering, 2016, 2016: 1-11. http://downloads.hindawi.com/journals/mpe/2016/3528952.pdf [21] 刘澜, 李新. 基于MFD的路网可扩展边界控制策略[J]. 公路交通科技, 2018, 35(9): 85-91. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201809013.htmLIU Lan, LI Xin. Scalable perimeter control strategy of road network based on MFD[J]. Journal of Highway and Transportation Research and Development, 2018, 35(9): 85-91. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201809013.htm [22] 张卫华, 陈森, 丁恒. 基于燃油消耗与交通效率的区域交通控制模型[J]. 交通运输系统工程与信息, 2016, 16(6): 74-80. doi: 10.3969/j.issn.1009-6744.2016.06.012ZHANG Weihua, CHEN Sen, DING Heng. The traffic control model based on efficiency and fuel consumption of the road network[J]. Transportation Systems Engineering and Information, 2016, 16(6): 74-80. (in Chinese) doi: 10.3969/j.issn.1009-6744.2016.06.012 [23] 张卫华, 陈森, 丁恒. 考虑边界交叉口交通拥堵的反馈阀门控制[J]. 控制理论与应用, 2019, 36(2): 241-248. https://www.cnki.com.cn/Article/CJFDTOTAL-KZLY201902009.htmZHANG Weihua, CHEN Sen, DING Heng. Feedback gating control considering the congestion at the perimeter intersection[J]. Control Theory & Applications, 2019, 36(2): 241-248. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KZLY201902009.htm [24] 廖南楠. 基于MFD的城市路网交通拥堵特性及门限控制方法研究[D]. 南京: 东南大学, 2017.LIAO Nannan. Research on traffic congestion characters and gating control of urban network based MFD[D]. Nanjing: Southeast University, 2017. [25] ZHANG Zhao, WOLSHON B, DIXIT V V. Integration of a cell transmission model and macroscopic fundamental diagram: Network aggregation for dynamic traffic models[J]. Transportation Research Part C: Emerging Technologies, 2015(55): 298-309. [26] XUE Zhengui, CHIABAUT N, LECLERCQ L. Effect of traffic modeling on control of traffic networks[J]. Transportation Research Record: Journal of the Transportation Research Board, 2016, 2560(1): 47-56. doi: 10.3141/2560-06 [27] 刘小明, 唐少虎, 朱凤华, 等. 基于MFD的城市区域过饱和交通信号优化控制[J]. 自动化学报, 2017, 43(7): 1220-1233. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201707011.htmLIU Xiaoming, TANG Shaohu, ZHU Fenghua, et al. MFD-based optimal control of oversaturated traffic signals in urban areas[J]. Journal of Automation, 2017, 43(7): 1220-1233. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201707011.htm [28] 常玉林, 袁才鸿, 孙超, 等. 基于改进元胞传输模型的城市路网实际阻抗计算方法[J]. 吉林大学学报(工学版), 2020, 50(1): 132-139. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202001015.htmCHANG Yulin, YUAN Caihong, SUN Chao, et al. Calculation method for actual impedance of urban network based on improved cell transmission model[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 132-139. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY202001015.htm [29] KALYANMOY D, AMRIT P, SAMEER A, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197. doi: 10.1109/4235.996017