Abstract
AbstractCOVID-19 has caused substantial negative impacts on transportation. In order to analyze the impact of residents’ choice of public transport mode during the post epidemic period, this paper uses the two binary logit model to calibrate the model parameters with SPSS software to study the impact of residents’ attributes, travel attributes, and risk perception attributes on the residents’ travel behavior. The research results show that: residents analyze public health emergencies according to their education level and make decisions based on their comprehensive family income level, the higher the income level, the more willing to travel by rail transit; With the increase in travel frequency, residents are more inclined to travel by bus, while with the increase of travel time, residents will be more inclined to travel by rail transit; The risk level of the epidemic has no significant impact on residents’ public transport travel, while residents’ understanding of the epidemic and travel susceptibility have a significant impact on public transport travel.KeywordsPost-epidemic periodPublic transportTravel modeBinary logit model
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
