Research On Optimization Of Headway Time Based On Real-time Control Of Public Transport In Collaborative Environment

Ground bus is an important part of urban public transport system,which undertakes the important functions of residents’ daily travel and rail transit connection.However,compared with rail transit,there are some problems in the ground bus,such as the right of way is not independent,the comfort is not high,the traffic volume is small,the bus headway fluctuates greatly,the punctuality rate is low,and the running time is prolonged.As a result,in recent years,the sharing rate of ground bus has decreased year by year in many cities of our country,and the rail transit is overloaded.Therefore,maintaining the stability of bus headway is the key to improve the punctuality rate and attractiveness of ground buses.Based on the vehicle road collaboration technology,this paper studies and constructs the bus headway optimization model and method of real-time speed control under the collaborative environment,which is of great significance to improve the operation reliability and service level of ground bus,and alleviate urban traffic congestion.Firstly,this paper had expounded the basic concept and influencing factors of bus headway,analyzes the process of bus headway optimization and clarifies the collaborative environment of bus headway optimization combined with the collaborative mode of bus headway optimization.Secondly,the process of bus real-time speed control and bus headway prediction is analyzed.The characteristic factors of bus headway and the advantages,disadvantages and application scope of conventional bus headway prediction model is studied.The BP neural network bus headway prediction model(FA-ANN)optimized by firefly algorithm is constructed and applied to the actual example analysis,The results show that: the average absolute error of FA-ANN model prediction results and the actual headway is 12.99 s,compared with the conventional BP dynamic prediction and static prediction results,it reduces36.60% and 54.40% respectively,demonstrating the improvement of the accuracy of the prediction model by the optimization algorithm.Then,the qualitative analysis of the optimized headway of bus real-time control is carried out,and the subjective influence of the implementation process of the optimized headway of bus real-time control on bus passengers is analyzed.The real-time speed control strategy with less subjective influence on bus passengers is selected to optimize the headway,and the calculation and optimization process of the optimized headway of bus are analyzed,the optimization model of headway is established,which has little subjective impact on passengers and good objective optimization effect.Finally,taking No.475 bus in the main urban area of Chongqing as an example,the objective optimization effect of the optimization model of headway is quantitatively analyzed through simulation examples.The results show that the real-time speed control of bus is better than the actual operation situation under the conditions of road traffic flow and bus lane without road traffic flow,the standard deviation of bus headway and departure interval is reduced by 32.56% and 83.98% respectively,which verifies the effectiveness of the bus headway optimization model based on the combination of subjective and objective.In this paper,the bus headway is taken as the research object.In the bus headway optimization model of real-time bus control in collaborative environment,two factors,small subjective impact on passengers and good objective optimization effect,are introduced.By using BP neural network,firefly algorithm,real-time bus speed control and other theoretical methods,qualitative and quantitative analysis is carried out Quantitative research on the model methods of bus headway prediction and bus real-time speed control optimization headway process in collaborative environment,to a certain extent,supplement the relevant theory of bus headway research.