Study On The Mechanism Of Multi-line Bus Bunching Based On Intelligent Bus Data

With the accelerated pace of life and the improvement of living standards,the level of domestic bus service is continuously decreasing,which is far from meeting the needs of passengers.The phenomenon of “large interval” and “bus bunching” often appear between different lines of vehicles,and the competitiveness of public transportation is weak.It is difficult to better guide the improvement of residents' travel structure,thus reducing the level of urban traffic congestion.In the previous related research,the phenomenon of two cars or more than two cars on the same bus line enter the bus stop at the same time was defined as “bus bunching”.Many scholars have done relatively complete research.Domestic research on bus bunching started late,and the domestic conventional bus operation system has more complex features such as high frequency,high repeatability coefficient and strong traffic flow.Therefore,it is of great significance to study the problem of cross-carriage between multi-line vehicles in China.Based on the research of Chengdu intelligent public transport data and single-line bus bunching,this paper studies the main influence mechanism of bus multi-line bus bunching from three aspects: multi-line bus bunching index description,influencing factor analysis and vehicle-to-station operation law.First of all,this paper summarizes the relevant research results in the past,combined with the actual domestic bus bunching,puts forward the key issues to be solved in this study.The logical relationship between the GPS data in the AVL data and the GPS data transmitted from the station to the off-site is indicated,and the flow of AVL data processing and division is proposed.Then,according to the AVL data of Chengdu public transportation,the method of creating the space-time trajectory map of multi-line public transportation vehicles is proposed.The evaluation index of multi-line bus bunching is constructed to describe the frequency,specific gravity and severity of the bus bunching.In this paper,the linear regression model is used to analyze the effects of the four main variables of the number of bus routes,the number of vehicles arriving at the station,the average dwell time of the station and the operating period on the multi-line bus bunching,and combine the results of multiple case studies to finally show the variables.The number of vehicles arriving at the station,the average dwell time of the station is the main contribution variable of the multi-line bus bunching,and there is a significant positive correlation between the multi-line bus bunching description indicators.Finally,under the conditions of different arrival rates,the probability distribution of bus-to-station queuing and the distribution of vehicle staying time are studied.The results show that under different conditions of arrival rate,the vehicle's queuing distribution in the station is “S”-shaped curve change,and the fitting effect with the built-in logistic function of Origin software is very good.As the arrival rate of the platform vehicles is getting higher and higher,the average time of staying at the station and its volatility are on the rise.