Study On Optimization Of Bus Timetable Based On Multi Source Data With The Consideration Of Transfer

With the development of China's social economy, the scale of the city has been expanding and private automobile possessive quantity has increased year by year, resulting in the increasingly serious urban traffic congestion and the decline in the quality of residents travel. By encouraging urban residents to use the public transport, traffic congestion can be effectively alleviated. As a result, many cities take "public transport priority" as the basic strategy of urban transportation development, and strive to improve the infrastructure construction and management level of public transport. Making bus timetable is an important part of making bus operation plan. The optimization of bus timetable is essentially to the rational allocation of limited public resource, and to achieve a win-win business interests of the passengers and the bus.At present, a lot of research has been done on the bus schedule optimization problems, including single line bus schedule optimization and multi line schedule coordination and optimization. These related research provided a lot of ideas and methods for reference, and inevitably there are some limitations, mainly embodies the following three aspects:1?The research results can't be directly applied to the improvement of public transport system, which is caused by the difference of the passenger flow data in research and practice.2?When considering the transfer, the concept of "transfer" is limited to the ground transportation system, without considering the transfer between rail transit and ground transportation.3?Only taking the passengers of transfer station as the research object, the coordination of non transfer passengers and transfer passengers and the benefit distribution of passengers and public transit operators are ignored.This paper focuses on the above three problems. First of all, the paper introduces the theory of the preparation of public transit time table, including the analysis of the principle, basis and method, and preliminary determine the research ideas of bus schedule optimization, which is using modeling optimization method to solve the optimal departure interval. Then the paper describes the process of obtaining line operation state data and passenger flow data by using multi-source data. The multi-source data includes bus GPS data, bus IC card data and geographic data. After the steps of original data acquisition, data pretreatment and data fusion, the multi-source data can provide the database support based on actual operation for bus schedule optimization. Then, in view of the limitations of the existing research methods, combined with the domestic and international research status, this paper proposes a bus schedule optimization model. In this optimization model, the decision variable is the departure interval and the objective function is to minimize the total system cost, which considering the waiting time cost of non transfer passengers, the waiting time cost of passengers and the operating costs of public transportation operators. On the basis of this model, this paper selects the particle swarm optimization algorithm to solve the model, which is developed rapidly in recent years. Finally, the rationality and feasibility of the theoretical method of the paper is further verified by the case of NO.376 in Shenzhen, and the results is analyzed which obtained good results.