RESEARCH ARTICLE


Impact of Integrated Multimodal Traveler Information on Auto Commuter’s Mode Switching Propensity



A.A. Memon1, *, M. Meng2, Y.D. Wong3, S.H. Lam4
1 Technical Cooperation Program of EU for Road Sector Development Program of Ethiopia, SMEC International (Pty) Ltd., Ethiopian Roads Authority, Addis Ababa, Ethiopia
2 TUM CREATE, 1 CREATE Way, #10-02 CREATE Tower, Singapore 138602, Singapore
3 Centre for Infrastructure Systems, School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
4 Transportation Infrastructure Office, University of Macau, Avenida da Universidade, Taipa, Macau, China


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© 2017 Memon et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Technical Cooperation Program of EU for Road Sector Development Program of Ethiopia,, SMEC International (Pty) Ltd., Ethiopian Roads Authority, Addis Ababa, Ethiopia; Tel: +251 11 663 2249; Email: ab_ahad@emirates.net.ae


Abstract

Aim:

Real-time traveler information affects auto commuter’s travel behavior.

Method:

An ordered probit model is used to analyze auto commuter’s mode switching propensity under influence of simulated real-time multimodal traveler information. A travel preference survey is administered to car drivers to gather individual commuter’s travel decisions under integrated multimodal traveler information.

Result:

It is shown that integrated multimodal traveler information can influence willingness of car drivers to switch mode of travel, while socio-economic characteristics also influence the mode choice decision.

Keywords: Integrated traveler information, Multi-modal transportation, Mode switching propensity, Probit model, Preference survey.