Research On Public Transport Scheduling Optimization Based On The Information Of Quasi-real-time Flow

Urban public transport system can normal and efficient operate or not, not only depends on roads, vehicles and other facilities conditions, but also on the level of regulation and management of operating level. To improve the operating management leve of the public transport company, we must to understand the features of the public transport, master data bus trip timely, accurate and comprehensive, can make scientific planning. Because of the lack of regular real-time traffic flow and information, the public transport companies operating status in our China is bad, passengers's waiting time is too long or vehicles loading with low rate。To improve public transport scheduling management level, the field of public transport scholars, both at home and abroad have done a lot of research, and also made some success.In this article, we mainly targeted on the smart scheduling optimization system of the public transport, and about how to deside the interval of the bus traveling, Namely: how to make use of bus IC card and related quasi-real-time information of some short-term forecast traffic flow, and based on multi-objective planning to build public tansport operators scheduling optimization model, and use GA-SA to optimize the parameters of operation scheduling. Details are as follows:Chapter I, the background of the study whice is about intelligent public transport scheduling optimization system, and the current situation of public transport scheduling study both at home and abroad, the research objective of this article and the application of technical route.Chapter II, the concept of the intelligent public transport system optimization system, the frame of real-time bus scheduling optimization system and quasi-real-time scheduling optimization system, and analysis the method whice is used in the bus scheduling optimization in the recent years. Passenger traffic flow forecast, including in the forecasting methods used by the scheduling and operations research in the use of scheduling optimization models and algorithms, as well as a summary of their advantages and disadvantages. Chapter III analyse the current situation and future development trends of public transport enterprises scheduling, summed up the problem in the traditional scheduling, and suggest the development direction in the future of Chang Chun City's public transport scheduling. At last concluded the traditional compilation method of vehicle scheduling's timetable for public transport enterprises.Chapter IV study on how to projecte the flow based on the quasi-real-time information. In this paper, we take small samples of the short-term public transport IC card data for analy, and proportion with the number of coin, through survey and calculated flow of information whice is quasi-real-time transit passenger traffic information.Chapter V based on multi-objective planning to build a bus operator scheduling optimization model. Use GA–SA algorithm to optimize the model parameters, at the last make an example to verify the model and algorithm. In this article, we make passengers have smallest cost for waiting car and standing in the car, public transport company have the smallest total cost of the variable operating, Minimum three objectives for the establishment of the bus operators constrained scheduling optimization model. In the algorithm choice, accordance to model of the intelligent public transport operators scheduling optimization is a nonlinear programming problem, the variables and constraints are many features, choose the GA-SA annealing algorithm. Papers presented the solving steps of GA-SA annealing algorithm. The results of examples about this analysis showed that the model and algorithm can meet to the objectives of the problem, it came to that the model and algorithm is effective and credible.Chapter VI is the summary and outlook. A summary for this article, and in according to the findings in the course of my research, we are giving the prospect of the next step we should to study.In this article, there are two focus parts: First, how to access to the quasi– real -time and how to project flow changes in the regulation of short-term flow; second, whice modle can used to public transport scheduling optimization.In this article, the main features of the innovation as follows: Use quasi- real- time data for basic data to prediction, in order to meet the changes of traffic flow ,we make the index chang to meet a real-time correction in the forecast, to overcome exponential smoothing method is unable to accurately predict traffic flow changes of the shortcomings.