Research On Bus Priority Control Based On Dynamic Travel Time Prediction Model

As China's economy continues to grow,the size of the city and the size of the population have been expanding,and the residents' car ownership has a substantial increase.The road gets wider and wider,the intersection becomes more and more complex,but the pace of infrastructure construction still can't catch up with the pace of the development of traffic.The contradiction between urban traffic supply and residents' travel demand is prominent,and the congestion is serious,however,due to the urban road has been planned and used for many years,there is no potential to widen the space.Easing traffic problems need to use limited space to play the maximum capacity,the bus is one of the effective methods to solve the traffic problems.At the same time,the development of information technology becomes more and more mature,we can acquire abundant traffic information through the technical means,its application in the bus control system can achieve a better control effect.In reality,most buses share the road with other vehicles,in the constantly changing transportation system,only to acquire the vehicle's dynamic information,with more accurate prediction of bus travel time,can we develop better bus control method and minimize the impact on other vehicles.On the other hand,bus delay in intersection far outweigh the delay in the road,this paper aims at reducing the total people delay of the bus at the intersection,establishes bus priority control method based on travel time prediction,the main research contents are as follows:Firstly,this paper summarizes the domestic and foreign research on the bus travel time and the bus priority control,on this basis,the paper introduces the concept,connotation and the benefits of bus priority.We elaborates categories of the bus priority and three main methods:active priority,passive priority and real-time priority.And the principle and applicable conditions of the priority control method are analyzed.Secondly,this paper analyzes the bus priority control need to acquire the information in three aspects: the operating information of public transport vehicles,the information of other social and the information of passengers.We compare the principle and advantages and disadvantages of various methods to acquire the information,and establish the systemic framework of information acquisition and processing.We propose a model for predicting bus travel time based on RBF neural network,and use an example to verify the model.Results show that the prediction's accuracy of the model in bus travel time is high and can be used in the bus priority control of travel time prediction step.Thirdly,based on the three priority control method of bus priority control,this paper calculates the total people delay at the intersection of the three methods,with the total people delay at the intersection as evaluating indicator,to set up benefit target.And the timing parameters are studied under the scheme of priority strategy to ensure that the priority control scheme can make the intersection get the overall benefit optimization.Finally,this paper takes an intersection in Chongqing as the experimental object,using the acquired real-time data to predict bus travel time,to compare the efficiency of the intersection under the bus priority control strategy with the efficiency under the original distribution,results show that the total people delay under the bus priority control strategy is smaller.We confirm that the RBF artificial neural network can predict the bus travel time more accurate,meanwhile,bus priority control model based on travel time predictioncan improve running efficiency of bus in the intersections,optimize the total people delay of the intersection.