Factors Affecting the Willingness to Use Automated Buses: A Survey from China

2020-01-5141

12/30/2020

Features
Event
3rd International Forum on Connected Automated Vehicle Highway System through the China Highway & Transportation Society
Authors Abstract
Content
With the development of autonomous driving technology, automated buses have begun trial operations in many cities around the world, and marketization has become an important issue. In order to explore the influencing factors of the public's willingness to use automated buses, two rounds of surveys were conducted. Firstly, the importance of the attributes of automated buses was studied, based on which questionnaires on willingness to use automated buses were designed. Using data from 266 questionnaires collected, a logistic regression model was established. Model results show that demographic variables and historical travel behavior characteristics will have a significant impact. Women are less willing to choose automated buses than men, and older people aged above 50 are more likely to use the mode. People who often use regular buses to travel have higher willingness to choose automated buses than people using other modes. Among people using other modes including private cars, subways, ride-hailing, bicycles, etc., those using private cars and bicycles have higher potential to become automated bus users, while ride-hailing and taxi users have the lowest potential. It is also found that being equipped with a driver, having dedicated lanes, short bus headways, low fares, and short walking distances will increase people’s willingness to use automated buses. The research results can provide a theoretical basis for improving the acceptance of automated buses. Suggestions for the operation and promotion of automated buses are put forward.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-5141
Pages
7
Citation
Xi, H., Wu, Z., Zhou, H., and Yi, M., "Factors Affecting the Willingness to Use Automated Buses: A Survey from China," SAE Technical Paper 2020-01-5141, 2020, https://doi.org/10.4271/2020-01-5141.
Additional Details
Publisher
Published
Dec 30, 2020
Product Code
2020-01-5141
Content Type
Technical Paper
Language
English