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Travel Mode Choice Analysis with Shared Mobility in Context of COVID-19
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology ; 22(2):186-196 and 205, 2022.
Article Dans Chinois | Scopus | ID: covidwho-1847860
ABSTRACT
To analyze the impact of COVID-19 on the travel mode choice behavior with diverse shared mobility services, this study designed the stated preference (SP) questionnaire for the multi-modal transportation system which include conventional travel modes, ride hailing, ride sharing, car sharing, and bike sharing. The mixed Logit models with panel data were proposed to investigate the travel mode choices before and during COVID-19. The influence differences of explanatory variables are compared, and the joint effects of perceived pandemic severity and mode choice inertia are examined. Based on the elasticity analysis, the mode choice preferences are predicted corresponding to different management policies under COVID-19 pandemic. The results indicate that the perception to pandemic severity has significant impacts on the ridership of ride sharing and car sharing, and the mode choice inertia obviously affects the usage of ride hailing, car sharing, and bike sharing. When the perceived pandemic severity reduces to 30%~50%, the strategy of increasing parking charge to 1.6~3.0 times would reduce the usage of private car to pre-pandemic condition, and the car sharing with lower close contact risk could become a main substitute. When the perceived pandemic severity is higher than 60%, the strategy of increasing the travel safety of ride sharing to 1.4~3.6 times would improve the ridership. Copyright © 2022 by Science Press.
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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: Scopus langue: Chinois Revue: Journal of Transportation Systems Engineering and Information Technology Année: 2022 Type de document: Article

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Texte intégral: Disponible Collection: Bases de données des oragnisations internationales Base de données: Scopus langue: Chinois Revue: Journal of Transportation Systems Engineering and Information Technology Année: 2022 Type de document: Article