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16-08-2022

A multinomial probit analysis of shanghai commute mode choice

Authors: Ke Wang, Chandra R. Bhat, Xin Ye

Published in: Transportation | Issue 4/2023

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Abstract

Commute trips account for a large portion of travel demand in peak hours and significantly influence the operation of urban transportation systems. In this paper, we apply a fully flexible multinomial probit (MNP) model for the analysis of commute mode choice behavior, and compare this MNP model with more traditional discrete choice models, including the multinomial logit (MNL), the cross-nested logit (CNL), the heteroscedastic independent MNP (HI-MNP), and the homoscedastic non-independent MNP (HONI-MNP). The two-variate bivariate screening (TVBS) approach, a recently developed analytical evaluation for the multivariate normal cumulative distribution (MVNCD) function, is employed. The sample for analysis is drawn from a web-based travel survey conducted in Shanghai. Overall, from a data fit perspective at, both the disaggregate and aggregate levels, the MNP clearly outperforms all the other four models, underscoring the importance of considering both heteroscedasticity as well as correlated error terms when estimating mode choice models. Policy implications are also examined and discussed.

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The main purpose of this paper is to compare the performance of alternative multinomial mode choice models (MNL, CNL, HI-MP, HONI-MNP) with that of the full MNP multinomial mode choice model for motorized commute modes that lead to traffic congestion. Further the market share of the walking mode is low in Shanghai due to job-housing imbalance considerations. Therefore, bicycling and walking are just modeled as one non-motorized mode in this paper.

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Title: A multinomial probit analysis of shanghai commute mode choice
Authors: Ke Wang
Chandra R. Bhat
Xin Ye
Publication date: 16-08-2022
Publisher: Springer US
Published in: Transportation / Issue 4/2023
Print ISSN: 0049-4488
Electronic ISSN: 1572-9435
DOI: https://doi.org/10.1007/s11116-022-10284-x

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