基于实时车流感知的端限量式单通道车辆通行控制方法
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摘要
针对限量式单通道双向通行控制问题,基于GPS车流感知数据提出了一种端限量式单通道双向自适应通行控制方法。通过在单通道及两端划设扫描区、等候区、单通道内三大类区域,利用GPS定位数据实时感知分析车辆在单通道两端行驶的10种状态,构建了单通道车辆通行控制策略分析模型,对车流数据进行动态汇总和饱和度分析,然后根据"按需分配"和"端总量控制"策略提出了一种自适应双向通行信号控制策略,在此基础上研发了端限量式双向通行自适应信号控制系统.最后利用某大型露天矿单道平硐进行了实例验证,应用表明:该方法能够有效控制单通道车辆的双向限量通行,避免了车辆运输过程中的行驶冲突,减少了车辆"空等"时间和油耗,提高了单通道通行效率,大大提高了车辆的运输效率.
In order to solve traffic conflict in narrow single channel, improve traffic efficiency and ensure traffic safety and adaptive control in traffic signal of single channel ends with traffic flow dynamic detection,a traffic control method for single channel with limited vehicles based on GPS real-time traffic flow has been put forward. Firstly, the three regions of scanning area, waiting area, single channel should be divided in single channel and ends. Using GPS positioning data, ten states of vehicle can be confirmed by real-time traffic flow analysis. The analysis model of single channel traffic control strategy is built to dynamically summarize the traffic flow data and analyze saturation of traffic flow. Then, the principles of "to each according to his needs" and "total quantity control at the ends" are adopted. A adaptive traffic signal control method is put forward. Finally, this method is applied in a single adit of large open pit to control traffic. The application shows that: it not only effectively controls two-way limited traffic of single channel,but also avoids traffic conflict of transport vehicles, reduces the "waiting in vain" time and vehicles' fuel consumption and greatly improve the traffic efficiency of vehicles.
In order to solve traffic conflict in narrow single channel, improve traffic efficiency and ensure traffic safety and adaptive control in traffic signal of single channel ends with traffic flow dynamic detection,a traffic control method for single channel with limited vehicles based on GPS real-time traffic flow has been put forward. Firstly, the three regions of scanning area, waiting area, single channel should be divided in single channel and ends. Using GPS positioning data, ten states of vehicle can be confirmed by real-time traffic flow analysis. The analysis model of single channel traffic control strategy is built to dynamically summarize the traffic flow data and analyze saturation of traffic flow. Then, the principles of "to each according to his needs" and "total quantity control at the ends" are adopted. A adaptive traffic signal control method is put forward. Finally, this method is applied in a single adit of large open pit to control traffic. The application shows that: it not only effectively controls two-way limited traffic of single channel,but also avoids traffic conflict of transport vehicles, reduces the "waiting in vain" time and vehicles' fuel consumption and greatly improve the traffic efficiency of vehicles.
引文
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[15]高云峰,韩皓,胡华.信号控制交叉口交通行为的简单二维元胞传输模型[J].系统工程理论与实践,2015,35(1):150-159.Gao Y F,Han H,Hu H.A simple two-dimensional cell transmission model:A dynamic representation of traffic at multiphase signals[J].Systems Engineering—Theory&Practice,2015,35(1):150-159.
[2]Zhang L,Zhu W.Delay-feedback control strategy for reducing CO_2 emission of traffic flow system[J].Physica A:Statistical Mechanics and its Applications,2015,428:481-492.
[3]Chao K,Chen P.An intelligent traffic flow control system based on radio frequency identification and wireless sensor networks[J].International Journal of Distributed Sensor Networks,2014,Article ID 694545,doi:10.1155/2014/694545:1-10.
[4]Tiaprasert K,Zhang Y,Wang X,et al.Queue length estimation using connected vehicle technology for adaptive signal control[J].IEEE Transactions on Intelligent Transportation Systems,2015,16(4):2129-2140.
[5]刘明剑,谭国真,魏欣,等.基于禁忌搜索的交叉路口自治车辆调度方法[J].中国公路学报,2016,29(2):123-129.Liu M J,Tan G Z,Wei X,et al.Autonomous vehicle scheduling method based on Tabu search at intersections[J].China Journal of Highway and Transport,2016,29(2):123-129.
[6]吴黎兵,聂雷,刘冰艺,等.基于双层管道模型的智能交通信号控制方法[J].计算机学报,2016,39:No.7.Wu L B,Nie L,Liu B Y,et al.Intelligent traffic signal control method based on a double tube model[J].Chinese Journal of Computers,2016,39:No.7.
[7]陈小红,钱大琳,秦雪梅,等.基于互补间题的混合交通信号配时优化模型[J].系统工程理论与实践,2010,30(1):184-191.Chen X H,Qian D L,Qin X M,et al.Complementarity problems-based optimization model for the signal timing under mixed traffic conditions[J].Systems Engineering—Theory&Practice,2010,30(1):184-191.
[8]刘文彬,李香宝,刘超群,等.交叉路口中一种智能的车辆实时调度算法[J].计算机应用研究,2016,33(4):1047-1049.Liu W B,Li X B,Liu C Q,et al.Intelligent vehicles real-time scheduling algorithm at intersection[J].Application Research of Computers,2016,33(4):1047-1049.
[9]安毅,宁滨,蔡伯根,等.GPS/CP车辆定位与交叉口冲突检测[J].交通运输工程学报,2013,13(1):104-113.An Y,Ning B,Cai B G,et al.Vehicle positioning using GPS/CP and intersection collision detection[J].Journal of Traffic and Transportation Engineering,2013,13(1):104-113.
[10]Tan H S,Huang J.DGPS-based vehicle-to-vehicle cooperative collision warning:Engineering feasibility viewpoints[J].IEEE Transactions on Intelligent Transportation Systems,2006,7(4):415-428.
[11]杨晓光,赵靖,马万经,等.信号控制交叉口通行能力计算方法研究综述[J].中国公路学报,2014,27(5):148-157.Yang X G,Zhao J,Ma W J,et al.Review on calculation method for signalized intersection capacity[J].China Journal of Highway and Transport,2014,27(5):148-157.
[12]Vasirani M,Ossowski S.A market-inspired approach for intersection management in urban road traffic networks[J].Journal of Artificial Intelligence Research,2012,43(43):621-659.
[13]张方伟,王炜,李志斌,等.城市普通道路与快速路出口衔接区域信号交叉口公交优先实施方法[J].系统工程理论与实践,2016,36(7):1786-1794.Zhang F W,Wang W,Li Z B,et al.Novel transit priority strategy for signalized intersection at connecting sections of ordinary road and rapid road in urban areas[J].Systems Engineering—Theory&Practice,2016,36(7):1786-1794.
[14]承向军,杜鹏,杨肇夏.基于多智能体的分布式交通信号协调控制方法[J].系统工程理论与实践,2005,25(8):130-135.Cheng X J,Du P,Yang Q X.A distributed and coordinated traffic signal control approach based on multi-agent system[J].Systems Engineering—Theory&Practice,2005,25(8):130-135.
[15]高云峰,韩皓,胡华.信号控制交叉口交通行为的简单二维元胞传输模型[J].系统工程理论与实践,2015,35(1):150-159.Gao Y F,Han H,Hu H.A simple two-dimensional cell transmission model:A dynamic representation of traffic at multiphase signals[J].Systems Engineering—Theory&Practice,2015,35(1):150-159.