An Operational State Evaluation Method For Isolated Urban Intersections

Urban signalized intersections are the bottleneck locations in urban traffic networks.Traffic flow is gathered,then directional separated at urban signalized intersections.The traffic operation condition at the intersections is so complex as to bring a series of problems,such as traffic delay that affects people’s travel efficiency,and high traffic accident rate.Therefore,it is necessary to accurately evaluate the real-time operation status of intersections,in order to learn the traffic operation status at intersections,so as to rationally distribute the traffic flow in time and space to realize the smooth operation of the transportation network.The main research contents of this thesis are as follows:First,the research progress of intersection operational state evaluation indicators,evaluation model construction and model optimization methods are summarized.Through comparative analysis,the evaluation index data that can be obtained by the video detection technology are compared to the traditional evaluation index data,and the extension matter element method and genetic algorithm in the optimization are identified,which supports the following research.Second,the evaluation index of the intersection’s operational state is determined.According to the traffic parameters that can be collected by the video detection technology,combined with the traffic flow characteristics at the urban intersections,the evaluation index of the intersection’s operational state,including the flow ratio,the speed ratio,the space occupancy ratio and the queue length ratio.Third,a comprehensive evaluation model is constructed.The AHP method is used to determine the index weight.An evaluation model of the intersection’s operational state is established.The index parameter values,index weights,and index value ranges are used as inputs to the evaluation model.The extension matter-element method was used to obtain the intersection’s operational score.Then,a method to optimize the evaluation index weigh is constructedt.This thesis put proposes a model of index weight optimization which takes the weights of the evaluation index as the constraints,and the difference between the evaluation model’s score and the expert’s score as the objective.Then,this thesis presents a method to solve the optimization model based on genetic algorithm.Finally,continuous intersections of a road section in Fengxian,Xuzhou are selected as the research object.According to the experiment,datas are obtained by simulating the road section with VISSIM.Based on the VBA language,the evaluation model of the intersection’s operational state is developed to evaluate the operational state of the intersection cycle by cycle.On this basis,the index weight optimization model based on genetic algorithm is used to adjust the weights across time.The results show that the evaluation method can better evaluate the operational state of the intersection,and can continuously adapt the model to the changing characteristics of traffic flow.In this thesis,the extension matter element method is applied to evaluate of operational state of isolated intersections,and the genetic algorithm is introduced to improve the adaptive ability of the evaluation model,which are significant to learn the real-time operational state of the intersection.