Understanding user perception and feelings for autonomous mobility on demand in the COVID-19 pandemic era

Abstract

New mobility-on-demand services together with the emerging technology of autonomous vehicles (AV) aim to revolutionize urban transportation systems, by introducing autonomous driving and sophisticated sharing and routing schemes for efficiently serving individual’s needs and requirements. On the other hand, the COVID-19 pandemic has disrupted travel patterns due to the emerging trends of social distancing and teleworking. In this paper, we aim at investigating users’ perception on autonomous vehicles, mobility on demand schemes as well as on the future transportation landscape using data collected through a questionnaire survey in the Metropolitan Area of Athens, Greece conducted after the first COVID-19 pandemic wave. First, a statistical analysis of the responses is performed and, then, a clustering approach is followed to identify user profiles based on daily mobility patterns and attitudes towards autonomous vehicles. Subsequently, the identified profiles are exploited in the development of a Bayesian Network to reveal interrelations between user profiling, attitudes and perceptions for future mobility services. Regarding the acceptance of Autonomous Mobility on Demand (AMoD) services, as well as travelers’ level of happiness concerning future scenarios of urban transportation, results have shown that the majority of travelers in Athens will be more than happy in the case where the entire transportation system is served with AMoD services.

Keywords

• Mobility-on-demand
• Autonomous mobility
• Questionnaire survey
• User profiling
• COVID-19
• Bayesian Networks