Research On Customized Bus Passenger Flow Analysis And Operation Strategy Optimization

The main problems of traditional bus service are lack of rationality of line planning,single operation mode,mainly considering the coverage rate of bus accessibility rate and so on,but often ignore the passenger travel demand and so on.With the continuous expansion and development of the city,the traditional bus mode is difficult to satisfy people’s fast and convenient.The demand for free travel,such as Czechoslovakia,comfort and so on.As an extension service of public transport,the custom public transport is set up based on the mobile Internet and the passenger travel demand.It has made up the defects of the traditional bus service mode.It is a new model for the development of diversified and differentiated public transport services,which is conducive to improving urban traffic and environment.Widespread concern,and related research has increasingly become a hot topic.However,the new problems encountered by the new mode of customizing public transport include the large difference between the data base of the custom bus passenger flow analysis and the traditional bus flow analysis data base,the traditional bus mode and the custom bus mode run parallel to the different vehicle scheduling problems.Therefore,this paper proposes a custom bus passenger flow analysis algorithm and a multi-purpose route scheduling algorithm,which is displayed in a visual way,so as to improve the custom bus seat rate,so as to improve the rationality and operation efficiency of the custom bus line planning.The specific contents are as follows:(1)In view of the problems existing in the traditional bus traffic analysis algorithm,a fuzzy clustering algorithm based on time series is proposed.Based on the historical data of ticket reservation through APP or We Chat,the passenger flow situation in the same period of time is predicted according to the different time period,so as to achieve the purpose of better line planning;according to the custom bus.The characteristics of reservation and temporary booking passenger flow,combining fuzzy clustering algorithm with similarity search to realize the mining of fuzzy time series,through the process of time series data transformation,prediction,classification,clustering,similarity search and so on,the derivation and application of custom bus passenger flow are realized.(2)The change of bus operation mode makes the function of public transportation,such as the overall rate of decision and the repetition rate,gradually decreases in the planning of the bus line,and becomes the mode of travel demand,seat reservation,online payment and inspection ticket.In order to meet the requirements of bus route planning and vehicle scheduling for a large number of passengers,the requirement of the actual operation of the fixed line is fully considered,and the thermal diagram of the custom bus travel demand needs to be set up and expressed in a visual way.This paper systematically proposes the construction method and steps of the travel demand heat map,and intuitively expresses the analysis result of passenger travel demand.(3)As the traditional bus operation mode and the custom bus mode run side by side in the actual operation process,the traditional operation scheduling algorithm is not applicable in the two modes.Therefore,according to the actual situation,this paper puts forward a multipurpose route scheduling algorithm to achieve the purpose of efficient and practical transportation to achieve efficient and practical transportation by the effective scheduling of passenger vehicles which provide service in the traditional operation mode and the custom bus operation mode according to the position,the number of seats,the time of scheduling and so on.(4)In order to verify the feasibility and accuracy of the proposed method,a statistical analysis was carried out based on the results of the customized bus operation in Guangzhou.This chapter takes historical data as the training sample,using March 2018 as the analysis data,the traditional bus passenger flow forecasting algorithm only achieved 53.89% accuracy,and the fuzzy clustering algorithm model based on time series in the custom bus mode has achieved 78.04% prediction accuracy.After the use of multipurpose line power scheduling algorithm to improve the user experience,such as punctuality,vehicle applicability,departure point rate and so on,the number of praise has been improved relative to the traditional methods,the rate of praise has reached 85.49%,and the 81.40% of the traditional scheduling method has been raised by 4.09%.The experimental results show that the algorithm model established in this paper can basically meet the data requirements of operation,management and so on,and can provide decision support for the custom bus route planning.