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Method for dynamically generating bus timetables on basis of Bayesian network models

A Bayesian network, dynamic generation technology, applied in the field of public transportation informatization, can solve the problem of inability to solve the chain reaction process of dynamic changes of public transportation schedules and other problems

Active Publication Date: 2015-02-25
新唐信通(浙江)科技有限公司
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AI Technical Summary

Problems solved by technology

[0006] It can be seen from the above that the existing research methods cannot solve the chain reaction process of the dynamic change of the bus schedule caused by random interference. We should start from the whole and reveal how changes in the external environment cause changes in passenger flow or travel time, and then affect how the dynamic adjustment process of the schedule occurs. , and the complex relationship between them, such as triggering, interfering, transforming and coupling, predicting the generation of bus schedule and its occurrence probability in the case of complex traffic environment changes

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  • Method for dynamically generating bus timetables on basis of Bayesian network models
  • Method for dynamically generating bus timetables on basis of Bayesian network models
  • Method for dynamically generating bus timetables on basis of Bayesian network models

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Embodiment Construction

[0043] Further description will be made below in conjunction with the accompanying drawings provided by the present invention:

[0044] Such as figure 1 As shown, the present invention provides a kind of dynamic generation method of bus timetable based on Bayesian network model, according to the process of traffic event occurrence, development and evolution, builds the two-layer microcosmic and macroscopic Bayesian network model of dynamic generation of bus timetable , to analyze the cause of the imbalance between transport capacity and traffic volume that affects the dynamic generation of bus timetables, take external environmental factors as input, analyze how they affect passenger flow or travel time changes, and then how to cause the imbalance between bus transport capacity and traffic volume, the output is The result of the maximum matching capacity of the timetable. The control input can control the change of some states. Based on this, the external environmental condit...

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Abstract

The invention relates to a method for dynamically generating bus timetables on the basis of Bayesian network models. The method includes screening microscopic and macroscopic factors affecting dynamic generation of the bus timetables; building the double-layer microscopic and macroscopic Bayesian network models for dynamically generating the bus timetables, and in other words, building the Bayesian network models for forecasting dynamic variation of bus environments and the Bayesian network models for dynamically generating the bus timetables; predicting transport capacity and transport volume occurrence probabilities of various routes under the condition of random disturbance and reasons for unbalance of the transport capacity and the transport volumes of the various routes; combining scheduling policies with one another and generating possible timetable schemes around the target for timely evacuating passengers; computing various indexes for evaluating the quality of the timetables from the points of governments, enterprises and the passengers and evaluating the quality of the timetables. The method has the advantages that a function of dynamically adjusting the timetables according to variation of the bus environments can be implemented, and accordingly technical support can be provided for daily bus operation management.

Description

technical field [0001] The invention relates to the technical field of public transport informationization, in particular to a method for dynamically generating a public transport schedule based on a Bayesian network model. Background technique [0002] The compilation of bus timetable is one of the core tasks of the daily operation of public transport. According to the spatial and temporal distribution characteristics of residents’ travel, the frequency and type of departures in each time period are reasonably organized and arranged, and the problem of the maximum matching of transport capacity and traffic volume is mainly solved. When random factors in reality cause changes in bus passenger flow or travel time, this will cause an imbalance in bus transport capacity and volume, and thus the bus dispatching scheme will fail. Therefore, it is of great theoretical value and practical significance to dynamically adjust the timetable according to the dynamic changes of the bus e...

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Application Information

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IPC IPC(8): G08G1/00G06F19/00
Inventor 魏明孙博周晨璨
Owner 新唐信通(浙江)科技有限公司
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