COLLABORATIVE OPTIMIZATION METHOD FOR BUS TIMETABLE BASED ON BIG DATA

The present invention relates to a collaborative optimization method for bus timetables based on big data, which belongs to the technical field of urban bus operation and management. Bus GPS data, IC card data and line station data are fused together to provide real-time operation data for the formulation of bus timetables, and a bus timetable optimization model considering transfer between buses and rail transit lines is proposed. In the model, by taking the departure interval of each time period as a decision variable and taking the minimum total system cost as an objective function, the waiting time cost of non-transfer passengers, the waiting time cost of transfer passengers, and the operation cost of bus operation enterprises are comprehensively considered. By means of the present invention, passenger flow data are acquired through multisource data fusion, a large number of manpower is saved, and the accuracy of data is increased. The rationality of compiling the bus timetable is increased by considering transfer between ground buses and rail transit lines. The bus timetable is optimized by establishing a data model. The model takes into account both the waiting time cost of passengers and the operation cost of enterprises, and realizes the coordination of benefits between passengers and enterprises.