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Research on travel path choice considering complex environment: theory, model and case.

Authors :
Wei Hang Cao
Jian Jiang
Source :
Journal of Intelligent & Fuzzy Systems; 2022, Vol. 43 Issue 6, p8109-8126, 18p
Publication Year :
2022

Abstract

In this paper, considering the heterogeneity of travelers' decision-making behavior caused by travel environment factors, thus affecting the choice of travel path, the theories and methods of travel path choice based on improved cumulative prospect theory (ICPT) in complex environment were proposed. On the basis of cumulative prospect theory (CPT), the value function was improved, and the parameter value range was enlarged. The nonlinear curve of value function and weight function of cumulative prospect theory was fitted through thousands of data tests and experiments. Then according to the decision preference, the decision makers were divided into different categories and the reference point value relationship of heterogeneous decision makers was found. In this paper, fuzzy travel time reference point and periodic dynamic risk degree reference point were set up, and a dynamic path selection model based on heterogeneous double reference point was established to improve the cumulative prospect value. Taking the highway network in Sichuan-Tibet region for example, the optimal path selection scheme of heterogeneous travel groups under the complex environmental factors such as debris flow and landslide in each time stage was studied, and the influence of preference parameter of travel time and risk degree on path choice was analyzed, and then the parameter sensitivity in the cumulative prospect theory (ICPT) was analyzed. The research results verified the rationality of the improved theory and method proposed in this study, which not only provide a new way of thinking for the study of travel path choice in complex environment but also provide theoretical guidance value for supporting regional traffic planning and construction in complex environment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
43
Issue :
6
Database :
Complementary Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
160553611
Full Text :
https://doi.org/10.3233/JIFS-220597