Research On Supply And Demand Of Public Bicycle Site Based On The Markov Chain Model

With the development of society, continuous expansion of urban scale, and sharp increase of vehicles, traffic congestion and environment pollution problems become more and more serious. As a green and environmental protection trip mode, the pubic bicycle has got more and more attention. However, problems of the public bicycle system such as no bicycle to borrow or no pile to return are remained to be solved, and accurate demand prediction of public bicycle station is the key to solve these problems. Traditional four-step method used to predict the demand of public bicycle station. Nevertheless, as for traditional four-step method, the smallest prediction cell is traffic zone. Yet a traffic zone usually contains several stations, so this method can not predict the station demand accurately. Therefore, the research of public bicycle station demand has significant meaning.Firstly, the paper introduced the current situation and the development of the public bicycle system in three parts:the layout of sites, vehicle scheduling and scale forecast.Secondly, the function and remaining problems of the public bicycle system was analyzed. This paper also researches the characteristic of using and the factors of demand influencing the system, according to the data of the public bicycle system from Zhongshan city.What’s more, the paper used Markov Chain to study the supply and demand of public bicycle station. The model for predicting the daily average demand of bicycle borrow-and-return was proposed. The result of prediction comparing with the actual swipe card data is tested, as well as error analysis. Then, the paper combined the prediction of daily average demand for bicycle borrow-and-return and the pile turnover in the station to build the model for station pile scale prediction.At last, we have a case study to give the specific steps of doing demand of daily average demand for bicycle borrow-and-return and doing pile scale prediction in the station, according the data from Zhongshan’s public bicycle systems.