摘要Strategies for inputting coordinated control signals in a freeway system are studied. Based on the symmetric, two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of a coordinated control section on a freeway with only one on-ramp segment and a mainline segment is established with access to real-time traffic information from an intelligent transportation system (ITS). The characteristics of traffic flow obtained by inputting coordinated control signals in the controlled section are discussed based on the results of simulations conducted using different control strategies. The effects of various traffic states, mainline upstream traffic volumes, and ramp demands on actual road capacity and traffic flow are analyzed by inputting no control signal, only on-ramp control signal, only variable speed limits signal, and speed limits, and ramp-metering signal. The simulation results indicate the following: the applicability of coordinated control as a main traffic management tool is better than that of other control methods; (2) the goal of decreasing the vehicle passing time, suppressing traffic jams, and enhancing road actual traffic volume can be realized by using the strategy of inputting different control signals under different traffic demands.
Abstract：Strategies for inputting coordinated control signals in a freeway system are studied. Based on the symmetric, two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of a coordinated control section on a freeway with only one on-ramp segment and a mainline segment is established with access to real-time traffic information from an intelligent transportation system (ITS). The characteristics of traffic flow obtained by inputting coordinated control signals in the controlled section are discussed based on the results of simulations conducted using different control strategies. The effects of various traffic states, mainline upstream traffic volumes, and ramp demands on actual road capacity and traffic flow are analyzed by inputting no control signal, only on-ramp control signal, only variable speed limits signal, and speed limits, and ramp-metering signal. The simulation results indicate the following: the applicability of coordinated control as a main traffic management tool is better than that of other control methods; (2) the goal of decreasing the vehicle passing time, suppressing traffic jams, and enhancing road actual traffic volume can be realized by using the strategy of inputting different control signals under different traffic demands.
基金资助:Supported by the National Natural Science Foundation of China (No.50478088);the Natural Science Foundation of Hebei Province of China (No.E2011202073)
通讯作者:
PANG Ming-bao, E-mail:pmbpgy@sina.com
E-mail: pmbpgy@sina.com
引用本文:
庞明宝, 蔡章辉, 杨敏, 张莎莎. 高速公路协调控制信号施加策略[J]. Journal of Highway and Transportation Research and Development, 2015, 9(1): 79-87.
PANG Ming-bao, CAI Zhang-hui, YANG Min, ZHANG Sha-sha. Coordinated Control Signal Input Strategies for Freeways. Journal of Highway and Transportation Research and Development, 2015, 9(1): 79-87.
[1] CHIEN C C, ZHANG Y P, IOANNOU P A. Traffic Density Control for Automated Highway Systems[J]. Automatica, 1997, 33(7):1273-1285.
[2] LIANG Xin-rong, LIU Zhi-yong, MAO Zong-yuan. Neuro-fuzzy Control for Speed Limit on Expressway and Its Simulation Study[J]. Journal of Highway and Transportation Research and Development, 2005, 22(11):123-125, 129. (in Chinese)
[3] ALLABY P, HELLINGA B, BULLOCK M. Variable Speed Limits:Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications[J]. IEEE Transactions on Intelligent Transportation Systems, 2007, 8(4):671-680.
[4] TIAN Q, HUANG H J, YANG H, et al. Efficiency and Equity of Ramp Control and Capacity Allocation Mechanisms in a Freeway Corridor[J]. Transportation Research Part C:Emerging Technologies, 2012, 20(1):126-143.
[5] VAN NES N, BRANDENBURG S, TWISK D. Improving Homogeneity by Dynamic Speed Limit Systems[J].Accident Analysis & Prevention, 2010, 42(3):944-952.
[6] HEYDECKER B G, ADDISON J D. Analysis and Modeling of Traffic Flow under Variable Speed Limits[J]. Transportation Research Part C:Emerging Technologies, 2011, 19(2):206-217.
[7] HEGYI A, DE SCHUTTER B, HELLENDOORN H. Model Predictive Control for Optimal Coordination of Ramp Metering and Variable Speed Limits[J]. Transportation Research Part C:Emerging Technologies, 2005, 13(3):185-209.
[8] CARLSON R C, PAPAMICHAIL I, PAPAGEORGIOU M, et al. Optimal Motorway Traffic Flow Control InvoLving Variable Speed Limits and Ramp Metering[J]. Transportation Science, 2010, 44(2):238-253.
[9] ZHANG Yong. Nonlinear Characteristics Analysis, Prediction, and Control of Traffic Flow[D]. Beijing:Beijing Jiaotong University, 2011. (in Chinese)
[10] PANG Ming-bao, HE Guo-guang, MA Ning. On-ramp Chaos Control of Freeway System with Fuzzy Delay Feedback Based on Genetic Algorithm[J]. China Civil Engineering Journal, 2009, 42(3):125-131. (in Chinese)
[11] ZHAO X M, GAO Z Y. A Control Method for Congested Traffic Induced by Bottlenecks in the Coupled Map Car-following Model[J]. Physical A:Statistical Mechanics and Its Applications, 2006, 366:513-522.
[12] NAGATANI T. Randomness Control of Vehicular Motion through a Sequence of Traffic Signals at Irregular Intervals[J]. Physics Letters A, 2010, 374(28):2823-2826.
[13] JIANG R, CHUNG E, LEE J W. Local On-ramp Queue Management Strategy with Mainline Speed Recovery[C]//Procedia-Social and Behavioral Sciences-8th International Conference on Traffic and Transportation Studies. Changsha, China:Elsevier, 2012:200-209.
[14] ZHANG Jing-jing, PANG Ming-bao, REN Sha-sha. Characteristics Analysis of Traffic Flow in Variable Speed Limit Section of Freeway Based on Cellular Automaton Model[J]. Acta Physica Sinica, 2012, 61(24):244-503. (in Chinese)
[15] REN Sha-sha, PANG Ming-bao, WANG Yan-hu, et al. Chaos Control of Freeway Mainline Using Variable Speed Limits with FNN Based on Subtractive Clustering[J]. Journal of Highway and Transportation Research and Development, 2012, 29(7):124-131.(in Chinese)
[16] WU Ke-fei, KONG Ling-jiang, LIU Mu-ren. The Study of Cellular Automaton NS and WWH Mixed Model for Traffic Flow on a Two-lane Roadway[J]. Acta Physica Sinica, 2006, 55(12):6275-6280. (in Chinese)
[1]
周星宇, 李红梅, 郑伟皓, 唐智慧, 杨丽君. 基于交互式BP-UKF模型的短时交通流预测方法[J]. Journal of Highway and Transportation Research and Development, 2019, 13(2): 56-64.
[2]
赵妮娜, 赵晓华, 林展州, 葛书芳. 主线分流互通立交指路标志版面形式研究[J]. Journal of Highway and Transportation Research and Development, 2019, 13(2): 90-102.
[3]
姚佼, 徐洁琼, 倪屹聆. 城市干道多时段协调控制优化研究[J]. Journal of Highway and Transportation Research and Development, 2018, 12(3): 60-70.
[4]
王东柱, 陈艳艳, 马建明, C. Michael WALTON. 车联网环境下的高速公路合流区协调控制方法及效果评价[J]. Journal of Highway and Transportation Research and Development, 2017, 11(4): 90-97.
[5]
戢晓峰, 张玲, 冯川. 多源出行信息影响下的路径选择行为仿真研究[J]. Journal of Highway and Transportation Research and Development, 2017, 11(1): 77-83.
[6]
王雁, 穆春阳, 马行. 基于Zernike不变矩与SVM交通标志的识别[J]. Journal of Highway and Transportation Research and Development, 2016, 10(3): 85-89.
[7]
张邻, 吴伟明, 黄轩为. 基于分层序列的相邻信号交叉口 控制系统动态优化模型[J]. Journal of Highway and Transportation Research and Development, 2016, 10(1): 85-91.
[8]
高剑, 张凡, 孙玲. 公路资产与交通安全的关系研究(II)[J]. Journal of Highway and Transportation Research and Development, 2015, 9(4): 91-96.
[9]
张邻, 黄选伟, 吴伟明. 机非混行驾驶行为博弈分析[J]. Journal of Highway and Transportation Research and Development, 2015, 9(3): 85-93.
[10]
张荣辉, 周佳利, 游峰, 周喜, 裴玉龙. 基于分级树状级联分类的双特征夜间行人检测[J]. Journal of Highway and Transportation Research and Development, 2015, 9(2): 77-83.
[11]
宋向辉, 李亚檬, 赵佳海, 王新科. 一种面向安全辅助预警的车辆相对位置判定方法[J]. Journal of Highway and Transportation Research and Development, 2014, 8(2): 88-92.
[12]
王东柱, 杨琪. 欧洲合作智能交通系统发展现状及相关标准分析[J]. Journal of Highway and Transportation Research and Development, 2014, 8(2): 81-87.
[13]
高剑, 张建栋, 罗梅村. 公路资产与交通安全的关系研究(I)[J]. Journal of Highway and Transportation Research and Development, 2014, 8(2): 99-104.
[14]
杨文丽, 杨蕴, 刘鸿伟. 基于出行者需求快速聚类的公路交通路径规划研究[J]. Journal of Highway and Transportation Research and Development, 2014, 8(1): 84-87.
[15]
王东柱, 陈艳艳. 基于浮动车停车点数据交叉口车辆排队长度计算方法[J]. Journal of Highway and Transportation Research and Development, 2013, 7(3): 84-89.
2015, Vol. 9 
