Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model

Understanding the impact of smartphone-based multimodal information (SMMI) on travellers' P&R (park-and-ride) choice behaviour is very limited so far. The purpose this study to better understand how SMMI, social network information, and individual characteristics influence mode choices. A stated preference experiment consisting one option two auto-driving routes was conducted collect car commuters’ data in Shanghai, China. panel mixed logit model utilized determine influencing factors. It found that model, accounting for correlations among repeated observations same respondent random taste, significantly outperforms cross-sectional multinomial terms goodness-of-fit. Specifically, travellers are highly sensitive offered by SMMI travel time, parking fare, crowding level subway cars, heterogeneities do exist preferences these In positive propensity online reviews about play a role promotion. addition, including gender, age, occupation, years driving, experience all contribute explaining P&R. Finally, elasticity analysis reveals commuters more satisfied with time than cross demonstrates substitution effect private cars.