A bus dispatching method based on real-time passenger flow forecasting

Abstract

The invention discloses a bus dispatching method based on real-time passenger flow prediction. The details are as follows. Step 1. Select a bus line arbitrarily and collect the number of people getting on and off the bus at each bus stop on the bus line within the vehicle operation time range; Steps 2. Select each stop in the upstream and downstream stops of the bus line in turn, and calculate the frequency of passenger flow increments of each train passing this station, the frequency of passenger flow increment of adjacent trains, and the occurrence of the previous train passing this station. According to the passenger flow increment, build a site passenger flow prediction and analysis model; Step 3, select the passenger flow increment of the adjacent trains with the highest probability; Step 4, establish a prediction analysis model of line passenger flow; Step 5, establish the relationship between the line's real-time passenger flow and dispatched departures Model; Step 6: Carry out dispatching and departure based on the relationship model between real-time passenger flow on the line and dispatching and dispatching.

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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