Saturated Flow Rate Of Urban Road Signalized Intersection Under Mixed Traffic Conditions

With the rapid development of the city scale,the urban road as the city aorta has also been rapidly developed.Signalized intersection is an important part of road traffic,especially urban roads,which has long been the focus of traffic managers and scholars.The vehicles in the signalized intersection in different directions,conflicts,acceleration and deceleration make the traffic flow especially chaotic,traffic congestion often occurs,therefore,the study of the traffic operation condition of the signalized intersection is the key to alleviate traffic congestion,to solve the bottleneck problem of traffic congestion.The saturated flow of signalized intersections is studied to improve the traffic efficiency and capacity of signalized intersections.At present,the research on the saturation flow rate of signalized intersections mainly starts from the independent analysis of a single influencing factor,ignoring the interaction between the influencing factors.Therefore,for the study of saturated flow rate at signalized intersections,a new correction coefficient model based on the interaction of influencing factors is proposed,and the average percentage error(MAPE)is used to compare the predicted value of the model with the observed value.Compared with the standard value,the error is greatly improved.Taking the interaction of influencing factors into consideration is of great significance for the study of saturated flow rate.The proposed method not only improves the accuracy of saturated flow rate,but also provides a new idea for the study of saturated flow rate.First of all,by referring to domestic and foreign literatures on vehicle conversion coefficient,saturation flow rate and traffic capacity of signalized intersections,the research idea of this paper is determined,that is,starting from the traffic flow operation characteristics of signalized intersections,to find a new vehicle conversion coefficient suitable for signalized intersections,and then carry out research on the saturation flow rate.Secondly,the vehicle conversion coefficient model is improved based on the headway method.The saturated headway of different vehicle types is used to replace the average headway to improve the accuracy of the model,and the specific conversion coefficient values applicable to urban road signalized intersections are obtained.The values of small cars,medium cars and large cars are 1.00,1.25 and 2.50 respectively.Then from different influencing factors,this paper selects lane width and cart ratio as the two influencing factors to carry out traffic investigation on six intersections in Banan District of Chongqing.Through the investigation of data mining,the influence of influencing factors on saturation flow rate and their interaction on saturation flow rate,a new saturation flow rate model is established.Finally,for the verification of vehicle conversion coefficient,VISSIM simulation is used to simulate the signalized intersection.Taking the queue length as the evaluation index,according to the simulation results,the vehicle conversion coefficient based on the improved headway model is more consistent with the actual operation of traffic flow at signalized intersections.For the empirical analysis of saturation flow rate,the mean percentage error(MAPE)is used to verify and compare the saturation flow rate model value and the standard value with the actual saturation flow rate value.The results show that the error of the model value is reduced from 13.25% to 7.41% compared with the standard value.The effectiveness of the proposed method is demonstrated by integrating other evaluation indexes of output documents,which can be used for reference in the future research of saturation flow rate based on the interaction of various influencing factors.