Bus departure scheduling method based on real-time passenger flow prediction

Abstract

The invention discloses a bus departure scheduling method based on real-time passenger flow prediction. The method concretely comprises the following steps that step 1, a bus route is arbitrarily selected, and the number of get-on and get-off people within the range of the bus operation time of the bus route at each bus stop is acquired; step 2, each bus stop of all the up and down stops of the bus route is selected in turn, and statistics of the passenger flow increment frequency of each bus passing through the stop, the passenger flow increment frequency of adjacent buses and the passenger flow increment generated by the previous bus passing through the stop is performed so as to construct a stop passenger flow prediction analysis model; step 3, the passenger flow increment of the adjacent buses of the highest probability is selected; step 4, a route passenger flow prediction analysis model is established; step 5, the relation model of the route real-time passenger flow and scheduled departure is established; and step 6, scheduled departure is performed according to the relation model of the route real-time passenger flow and scheduled departure.

Description

technical field [0001] The invention belongs to the field of bus intelligent dispatching, and in particular relates to a bus dispatching method based on real-time passenger flow prediction. Background technique [0002] The bus passenger flow is of great significance to the intelligent transportation system. Through accurate quantitative data, it is possible to know the passenger flow of each time period, each bus, and each station. Using these data, the advantages of the dispatching system can be used to make public resources more efficient. Full use. Bus operation managers can use these accurate statistical data to provide practical and scientific solutions for public transport operation management, passenger flow planning, scheduling, and technical support. [0003] In recent years, although some scholars have devoted themselves to studying the relationship between bus passenger flow and bus dispatching system, and established some statistical analysis models, most of th...

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Problems solved by technology

[0004] The current statistical analysis models and algorithms have the following defects: (1) There is no effective forecasting model for bus real-time passenger flow. The existing passenger flow analysis model is based on historical passenger flow information statistics, and its main function is statistical analysis rather than prediction. No real-time bus passenger flow prediction method is proposed

(2) The relationship model between the real-time passenger flow of the bus and the real-time departure of vehicles on the bus line has not been established, resulting in the inability to schedule the departure of bus vehicles through real-time passenger flow

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