Research on the willingness of autonomous driving ride-sharing travel based on user experience
With the rapid advancement of science and technology,autonomous driving technology has experienced rapid development.In order to alleviate traffic congestion,ride-sharing in autonomous driving mode seamlessly integrates shared autonomous vehicles with dynamic carpooling.It provides travelers with a broader range of on-demand transportation services while also actively exploring green transportation and sustainable development.In this research,the experience of autonomous driving serves as the foundational basis for a questionnaire survey targeting commuters.The aim is to ascertain their daily travel patterns,perspectives and attitudes towards autonomous driving,inclination to participate in ride-sharing within autonomous vehicles and personal socio-economic attributes.Building upon this foundation,TransCAD is utilized to create willingness models for autonomous driving ride-sharing for both pre-experience and post-experience travelers,providing insights into the ride-sharing preferences of private car commuters and public transport commuters in autonomous driving mode.The results indicate that there is a significant difference between private car and public transport commuters'willingness to ride-sharing.The willingness of commuters to ride-sharing in autonomous driving mode in an actual open road traffic environment is influenced by daily commuting travel factors,autonomous driving awareness levels,attitudes towards autonomous vehicles,ride-sharing attitudes,and ride-sharing related factors.The autonomous driving ride-sharing experience resulted in a significant increase in commuters'awareness level of autonomous driving.This study provides a theoretical foundation for traffic management while simultaneously offering solutions to promote autonomous driving ride-sharing and alleviate traffic congestion issues.
autonomous drivingwillingness to ride-sharingexperienceBL model
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