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03.07.2019 | Ausgabe 6/2019

Transportation 6/2019

Investigating user perception on autonomous vehicle (AV) based mobility-on-demand (MOD) services in Singapore using the logit kernel approach

Zeitschrift:
Transportation > Ausgabe 6/2019
Autoren:
Yutong Cai, Hua Wang, Ghim Ping Ong, Qiang Meng, Der-Horng Lee
Wichtige Hinweise
Disclaimer:  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of the Singapore Ministry of Transport, Urban Redevelopment Authority, Land Transport Authority, Ministry of National Development and National Research Foundation, Prime Minister’s Office, Singapore.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

The rapid development of autonomous vehicles (AV) in recent years has drawn the attention of numerous countries in terms of its feasibility for use and deployment as individually-owned vehicles or for large-scale fleet planning and deployment as a mobility-on-demand (MOD) service. Singapore is no exception to this global trend and in her pursuit to be smart and car-lite, numerous efforts are made to have AV trials in place and test out their potential deployment in the city state. As one of the many prerequisites of AV planning, public perception on AV plays a vital role when designing any potential AV deployment scheme. As such, a stated preference survey comprising both online survey and field interviews/surveys, was performed island-wide to understand how commuters in Singapore perceive about different AV-based MOD modes. The logit kernel model is adopted to determine how different preference attributes and key demographic indicators can affect the use of AV-based MOD services over other existing first- and last-mile connection modes. The model results have identified how demographics such as gender, age, housing type, education level and income level can influence the travel mode choice. Also, the impacts brought by individuals’ stated preferences over convenience, privacy and familiarity of ride-hailing apps are also investigated. Such findings can provide useful insight in planning future car-lite towns and implementing AV-based MOD services in these towns.

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