Research On Feature Analysis And Optimum Discrimination Method Of Long-distance Bus Line Based On Intelligent Bus Data

As the scale of urban development continues to expand,the radiation capacity increases,and urban public transportation lines become longer and longer,especially the conventional bus lines extending from the city center to the surrounding areas.Such lines usually have some operational problems and are rapidly applied in current big data.In the development environment,the intelligent public transportation system represented by the Automatic Vehicle Positioning System(AVL)and the Automatic Billing System(AFC)emerged as the times require,which provides reliable data support for public transportation research.This paper mainly uses the historical data of intelligent public transportation to analyze and analyze the data,and compares the difference between the super long line and the conventional line from the aspects of passenger demand characteristics and operational characteristics,and builds a set of optimization and selection methods for ultra long lines based on its characteristics.Firstly,this paper briefly introduces the data structure of IC card data and AVL data in the intelligent public transport system.Based on the existing literature research and previous practice,this paper briefly describes the calculation rules of passenger travel OD on bus routes,and then introduces the research.The steps required to extract the required bus route map and analyze the data required for passenger demand characteristics.Secondly,this paper defines the scope of the super long line and analyzes the difference between the basic characteristics of the super long line and the conventional line.Thirdly,the paper digs deeper into the data,and compares the differences between passenger demand characteristics and operational characteristics from the macro and micro aspects.Selects the passenger flow section imbalance coefficient,average distance,average utilization coefficient,travel time reliability,and headway time.Quantitative analysis of indicators such as stability shows the difference in line length in bus operations.Finally,in order to solve the operational problems highlighted by the super long lines,clustering analysis of super-long line based on average mileage utilization coefficient and passenger flow rate is presented in this paper,and constructs a set of optimization discriminant selection methods for different types of super long lines,and describes the operation of each optimization method.A case study was conducted to test the effectiveness of the optimization method.The research results of this paper can help to understand the value and corresponding operational problems of the super long bus lines in the city,and provide practical decision guidance for the operation managers.