|Table of Contents|

Logit model for travel mode choice with traffic capacity constraints(PDF)

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

Issue:
2024年2期
Page:
115-122
Research Field:
交通工程
Publishing date:

Info

Title:
Logit model for travel mode choice with traffic capacity constraints
Author(s):
CHEN Bo;  ZHAO Chun-jian
(College of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China)
Keywords:
traffic engineering;  transportation corridor;  Logit model;  traffic capacity;  penalty factor
PACS:
U491.14
DOI:
10.19721/j.cnki.1671-8879.2024.02.011
Abstract:
In order to improve the accuracy of traffic demand forecasting for passenger transportcorridors, addressing the shortcoming that the traffic capacity constraints are not adequatelyconsidered in the traditional passengers' mode choice models, the mechanism of passengers'mode choice and constraints from traffic capacity were deeply analyzed, and a penaltyfactor was introduced through the utility function optimization of the classical MNL model, tocharacterize the constraints of traffic capacity on passengers' mode choice, a constrainedMNL model was proposed, and the corresponding algorithm was designed to forecast the share ofeach transportation mode. The XiBao(Xi'an to Baoji)passenger corridor was taken as anexample to verify the superior performance of the constrained MNL model by comparativeanalyzing the forecasting results of the two models. The results show that in the process ofpassengers' mode choice, the constraints of traffic capacity are universal, which is an importantfactor that cannot be ignored for effective traffic demand forecasting, the constrained MNL modeltakes into account the impact of traffic capacity on passengers' mode choice, which is more in linewith the decision-making process of passengers' mode choice, and provides a reliable guaranteefor improving the accuracy of traffic demand forecasting from the mechanism. The penaltyfactor reflects the impact of traffic capacity constraints on passengers' mode choice, and representsthe decline in transportation service quality and the loss of passengers' utility. Through thereasonable assignment of the penalty factor, it can redistribute the passengers' choice probability,effectively simulate the shift of passengers' mode choice and control the probability ofpassengers' mode choice. Compare with the traditional MNL model, the constrained MNLmodel shows better performance, which can always control the forecasting results within theupper limit of the share determined by the traffic capacity, and the results are realistic, scientificand effective, which can provide reliable data support for the optimization of the network layoutand the design of the transportation organization.2 tabs, 6 figs, 30 refs.

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Last Update: 2024-03-01