Abstract
COVID-19 has had a significant impact on global transportation. While extensive research has focused on its influence on public transit and shared travel, the changes in overall vehicle travel demand remain under - explored. This paper analyzes the magnitude, duration, and driving factors of the impact of COVID-19 on urban overall vehicle mobility. We introduced the Prophet time series model, a suitable tool for time - series prediction in this context, to predict vehicle mobility without the pandemic. By comparing the predicted and real values, the mobility loss was derived. Multiple linear regression was then applied to deeply explore the causes of this loss, with a particular focus on the interaction effects of the strictness of regulatory orders and public fear. A large-scale dataset with over 4 billion raw data from multiple sources was used for empirical analysis. Results indicate that 29.66% of urban vehicle mobility loss occurs during the national outbreak period. The factor representing nationwide confirmed cases has a positive lagging effect on travel mobility loss, with a lag time of around seven days. The loss of urban motorized travel demand is largely due to the interaction of perceived risks and control policies.