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Bicycle-mode traveling selection forecasting method based on activity chain mode

A technology of travel prediction and activity chain, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve problems such as not considering the impact of residents

Inactive Publication Date: 2013-05-22
SOUTHEAST UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing research only considers the individual's preference for bicycle use in a single trip, and does not consider the influence of residents' daily activity patterns on the choice of bicycle travel.

Method used

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  • Bicycle-mode traveling selection forecasting method based on activity chain mode
  • Bicycle-mode traveling selection forecasting method based on activity chain mode
  • Bicycle-mode traveling selection forecasting method based on activity chain mode

Examples

Experimental program
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Effect test

Embodiment 1

[0067] Step (1) is used to predict the travel demand of urban residents in Bengbu City who choose bicycles. Bengbu City is located in the northern part of Anhui Province, with an urban area of ​​601.5km2 and a population of 914,300 at the end of 2006. Bengbu City is a typical group city. Including the central group, the northern group and the eastern group, it is divided into 98 traffic small groups. Random sample household questionnaire survey is used, and questionnaires are distributed according to the population ratio of the district. The content includes the individual characteristics of travelers, family characteristics, typical working day travel activities and methods. Selection, individual attributes mainly include the traveler’s gender, age, occupation, education level, etc., family characteristics mainly include family structure and size, means of transportation, family income, etc., travel attributes include land characteristics, travel distance, etc., and survey data...

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Abstract

The invention discloses a bicycle-mode traveling selection forecasting method based on an activity chain mode. The forecasting method includes the steps that the data survey is carried on a situation of resident traveling, and the survey result is managed and added up; a selecting mode of the resident traveling in a day in the data survey result is extracted, and the traveling mode is carried out on a variable virtual operation and a coding operation; a correlated variable in the activity chain mode is input to multi-term logit models, and a coevolution logit model can be obtained through calculating; the calculated coevolution logit model is carried out on iterative operation, and two selecting results of traveling modes are recorded; the two selecting results of the traveling modes are carried out on statistics and analysis, the prediction accuracy is carried out on contrastive analysis. By the statistics and the analysis of the vehicle selection of residents in urban, the proportion of the bicycle-mode traveling selection can be accurate to forecast, so that the urban traffic planning and the decision of the policy can be provided with the scientific and reasonable guidance.

Description

technical field [0001] The invention relates to the technical field of traffic demand prediction and traffic planning, in particular to a travel prediction method based on an activity chain model for selecting a bicycle mode. Background technique [0002] At present, with the acceleration of my country's urbanization process, urban space expansion, urban population size and urban road motorization level have all changed accordingly, especially in the urban passenger transport system. In the rapid urbanization, the urban passenger transport system has gradually exposed a series of negative problems such as traffic congestion, energy consumption, and air pollution. [0003] How to optimize the urban passenger transportation system is the key to alleviating urban traffic congestion and energy saving and emission reduction, and bicycles have the advantages of flexibility, no pollution, no energy consumption, and less road resource occupation in short-distance travel, so bicycles...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 李志斌刘攀王炜曹玮
Owner SOUTHEAST UNIV
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