Analysis On Running Data And Research On The Intelligent Vehicle Scheduling For Public Bicycle System

The public bicycle system plays an important role in short-distance traffic and solves "the last mile problem" of bus transportation effectively. The overall service level of the urban public transportation could be enhanced by the public bicycle system. At present, the phenomenon of "no-bicycle" and "no-parking" often occurs in the public bicycle system. Therefore, the analysis on the state of public bicycle system rental points can master their running rules and design reasonable scheduling scheme. This will help the reasonable dispatch of the public bicycle to be able to alleviate the imbalanced contradiction. It also can solve the problem of "no-bicycle" and "no-parking", and improve the service level of public bicycle system.First of all, in order to mine the running law of public bicycle system, get the trip group law through public bicycle system and improve some current problems existing in the public bicycle system, a spatial analysis method is developed. Taking public bicycle system of Hangzhou as an example, the characters including the rental behavior of users, time distribution of and space distribution of public bicycles needs are analyzed based on public bicycle system operational data of four years. Meanwhile, different operating characteristics of the system in working days, weekends of normal weather, holidays and four seasons of a year and bad weather (rainy, snowy, high temperature) are compared. The method provides accurate data basis for mastering the public bicycle trip group law of residents of Hangzhou and formulating public bicycle scheduling scheme.The method of clustering division for public bicycle scheduling regional based on association rules is proposed to solve current problems that Hangzhou public bicycle system does some scheduling only by administrative division. According to the self-liquidity of public bicycle among rental points, taking use of Hangzhou public bicycle system running OD data, association rules are used to have greater relevance points into a single collection, and the method of spatial clustering division is used to the collection to generate final district. Taking Hangzhou public bicycle rental points as an example, the division method is used. The result indicated that the method is effective and practical.During the public bicycle system’s vehicle scheduling process, the bicycle has mobility as a type of transport, thus public bicycle system’s vehicle scheduling is a superposed result of motor vehicle scheduling and bicycle self-demand flow. Therefore, a natural hybrid scheduling model is proposed. The multi-selection weighting model that lowest cost is the goal is established based on meeting public bicycle system naturally scheduling. The rolling horizon scheduling algorithm is applied to obtain real-time information of points, and the improved genetic algorithm is used to solve scheduling vehicles’ optimal path within each cycle.Finally, based on B/S architecture, the software system of the data analysis and intelligent scheduling system for public bicycle system is design and developed by J2EE and Oracle. The experimental result indicated that scheduling method proposed in this paper has good performance in optimizing the quantity of bicycles in the public bicycle system. And "the returning problem" and "the lending problem" of the public bicycle can be alleviated.