Big data based bus route time table collaborative optimization method

Abstract

The invention relates to a big data based bus route time table collaborative optimization method, and belongs to the technical field of urban bus operation management. Bus GPS (global positioning system) data, bus IC (integrated circuit) card data and route station data are fused and processed into a bus time table to provide actual operation based data support, and a bus time table optimization model considering rail transit transfer is provided. The model takes departure intervals at each time period as decision variables, takes minimum total system cost as an objective function, and comprehensively considers waiting time cost of non-transfer passengers, waiting time cost of transfer passengers and operating cost of bus operating enterprises. Passenger flow data are obtained through multi-source data fusion, a lot of manpower is saved, and accuracy in data is improved. By the consideration of routine bus system and rail transit transfer, reasonability in bus time table preparation is improved. A data model is set up to optimize the bus time table, waiting time cost of passengers and enterprise operating cost are both taken into consideration, and coordination in passenger and enterprise profits is realized.

Description

technical field [0001] The invention belongs to the technical field of urban public transportation operation management, relates to the compilation of bus timetables, the fields of ITS intelligent transportation system and particle swarm algorithm, and particularly relates to the technical method of big data mining and fusion processing. Background technique [0002] Yang Xiaoguang's "Research on the Shortest Bus Transfer Time Scheduling Based on ITS Environment". A linear programming model is established with the shortest bus transfer time as the goal, and the theoretical significance and practical value of this method are proved by examples. Liu Huanyu's "Research on Reliability-Based Design and Optimization of Bus Schedules" established a reliability-based bus schedule with the constraints of punctuality, travel time reliability, and service interval reliability, and with the goal of maximizing social welfare. However, there are three main problems in the existing resear...

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Problems solved by technology

Liu Huanyu's "Research on Reliability-Based Design and Optimization of Bus Schedules" established a reliability-based bus schedule with the constraints of punctuality, travel time reliability, and service interval reliability, and with the goal of maximizing social welfare. However, there are three main problems in the existing research. First, most of the passenger flow data used are obtained through manual investigation, which n

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