Automation technology and the sharing economy have brought changes to transportation, such as the appearance of shared autonomous vehicles (SAVs). This paper proposes a mode choice model combining the latent class model (LCM) and discrete choice model (DCM), to analyze choice behavior for SAVs, and identify factors that influence the preference for SAVs. A stated preference survey was conducted to obtain data of four aspects. Considering the first three aspects of data as manifest variables, respondents are classified into four classes by LCM. The utility is formulated for these four classes and calibrated by multinomial logit (MNL) and mixed logit (MIXL) model. Estimation results show that the proposed latent class approach performs better than the traditional MNL model in explanation ability, and influencing factors for each class are different. Results imply that the preference for SAVs differs across classes, and the preference for various modes differs across modes.
Choice Behavior Analysis for Shared Autonomous Vehicles: A Latent Class Approach
20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)
CICTP 2020 ; 3987-3998
09.12.2020
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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