BIG DATA BASED BUS LINE SCHEDULE COLLABORATIVE OPTIMIZATION METHOD

摘要

Provided is a bus line schedule collaborative optimization method based on big data, belonging to the technical field of urban bus operation and management. Bus GPS data, bus IC card data and line stop data are integrated and processed to provide the bus schedule with data support on the basis of actual operation. Meanwhile, a bus schedule optimization model in consideration of transferring to a rail transit is proposed. The model takes a departure interval of each time period as a decision variable and takes a minimum system total cost as an objective function, taking into consideration waiting time costs of both transfer and non-transfer passengers, as well as operation costs of bus operators. Passenger data is obtained through multi-source data fusion, thereby saving manpower and improving data accuracy. By taking into account the ground bus and rail transit transfer, the rationality of bus schedule preparation can be improved. And by establishing a data model to optimize the bus schedule, and taking into account of both the passenger waiting time costs and enterprise operating costs, the interests of passengers and enterprise can be coordinated.