城市交通控制与诱导协同的双层规划模型  

Bi-level programming model for cooperation of urban traffic control and traffic flow guidance

作　　者：孙智源[1] 陆化普[1] 张晓利[2] 屈闻聪 

机构地区：[1]清华大学交通研究所,北京100084 [2]交通运输部科学研究院,北京100029

出　　处：《东南大学学报（自然科学版）》2016年第2期450-456,共7页Journal of Southeast University：Natural Science Edition

基　　金："十二五"国家科技支撑计划资助项目(2014BAG01B0403);清华大学苏州汽车研究院(吴江)返校经费课题资助项目(2015WJ-B-02);北京市优秀人才培养资助项目(2014000020124G071)

摘　　要：为了均衡城市交通流的时空分布,以定时控制与战略诱导协同为研究对象,提出了一种城市交通控制与诱导协同模型.首先,建立了双层规划模型,上层模型以交叉口车均延误最小为目标,嵌入不同相位模式的定义约束,以实现信号控制优化;下层模型为用户均衡模型,引入虚拟路段表示交叉口延误对交通流分配的影响.然后,提出了一种启发式迭代优化算法对双层规划模型进行求解,其中,上层模型应用遗传算法求解,下层模型应用迭代加权法求解.算例研究结果表明:该协同模型减少了路网中的总旅行时间,解决了交叉口车均延误时间较多的问题,可实现城市交通流的时空均衡分布.In order to balance the spatial-temporal distribution of urban traffic flow,a model for the cooperation of urban traffic control and traffic flowguidance is established by taking collaboration between timing control and strategic guidance as the research objects. First,a bi-level programming model is put forward. Aimed at the minimization of the average vehicle delay of intersections,the upper level model embeds definitional constraints of different phase modes to realize the traffic signal control optimization. The lower level model is a user equilibrium model with the introduction of virtual roads to reflect the effect of the intersection delay on traffic assignment. Then,a heuristic iterative optimization algorithm（ HIOA） is presented to solve the bi-level programming model. The upper level model is solved by the genetic algorithm,and the lower level model is solved by the method of successive averages. The results of the case study showthat the proposed model can reduce the total travel time of the road network,solve the problems of high vehicle delay of intersections,and realize the spatial-temporal balanced distribution of urban traffic flow.

关 键 词：交通工程 交通控制 交通流诱导 智能协同 双层规划 

分 类 号：U491.1[交通运输工程—交通运输规划与管理]