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Trip distribution forecasting method of intercity-travel(PDF)

长安大学学报(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2017年05期
Page:
102-112
Research Field:
交通工程
Publishing date:

Info

Title:
Trip distribution forecasting method of intercity-travel
Author(s):
ZHU Hong-guo ZHANG Yi-yi MA Zhuang-lin HU Da-wei
1. School of Automobile, Chang’an University, Xi’an 710064, Shaanxi, China; 2. Guangdong Highway Transport Administration, Guangzhou 510075, Guangdong, China; 3. Shenzhen Urban Transport Planning & Design Institute, Shenzhen 518058, Guangdong, China
Keywords:
traffic engineering intercity-travel trip distribution forecasting urban location advantage factor Furness model
PACS:
U491
DOI:
-
Abstract:
In order to predict the trip distribution of intercity-travel without the current accurate OD matrix. Firstly, the urban location advantage factor was introduced based on location theory method and urban land use attributes and socioeconomic attributes. The city’s quality factor was determined by the city’s own prosperous degree, the city’s attractiveness factor was determined by the degree of urban land use, and the relative accessibility of the city was determined by the travel time between cities. Secondly, the urban location information was quantified from two aspects of the city’s aggregation scale factor and accessibility on the basis of the above mentioned three types of data. The city’s production location impact factors and attract location factor were respectively obtained, and the trip distribution probability matrix of different cities was obtained by the improved gravity model. Thirdly, the trip distribution of different cities was forecast by Furness model. Finally, the trip distribution forecasting of the Pearl River Delta Region, including nine cities, was taken as an example based on the above model. The results show that city’s aggregation scale quality factor can be quantified by socioeconomic indicators, accessibility between cities can be quantified by the reciprocal of the time needed for transportation between cities. The improved gravity model doesn’t need the trip distribution matrix of the base year, and the trip distribution probability matrix of intercity-travel can be obtained by production factor, attract location factor and relative accessibility (reciprocal of travel time). According to Furness model, after times of iterative calculation, the final trip distribution matrix can be obtained. The trip distribution forecasting method mentioned in this paper can simplify the collection of basic data and greatly reduce the workload of traffic survey of intercity residents. So it has extensive applicability.

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Last Update: 2017-10-16