Modeling of Onboard Activities: Public Transport and Shared Autonomous Vehicle

The continuous development in technology allows to have fully autonomous vehicles (AVs) on the market. Travelers are interested in maximizing their utility onboard by involving themselves in multitasking. Does choosing a particular type of multitasking determine what type of transport mode to be used? Several studies are conducted on conventional transport modes (CTMs); however, scarcely can be found on AVs. A stated preference (SP) survey including sociodemographic and trip characteristics as well as discrete choice experiments (DCEs) is used. The impact of multitasking on travel behavior is assessed, where multitasking is divided into six types of activities based on the characteristics of an activity (i.e., active, or passive activity). The random utility theory approach including the discrete choice modeling is applied, where transport choice models for the shared autonomous vehicle (SAV) and public transport (PT) are developed considering time, cost, and multitasking availability. The results demonstrate that each onboard activity has a different impact on the transport mode choice, and the social media activity has the largest positive, while the only writing activity shows a negative impact on the transport mode choice. Moreover, the impact of travel time on multitasking is higher than that of the travel cost. Additionally, the changes in the travel time and the travel cost do not show strong and high differences between onboard activities. SAV is more affected by a change in the onboard activities, the travel time, and the travel cost than PT. In conclusion, the results show that inside urban areas, PT is more likely to be used than SAV concerning the multitasking possibility, the travel time, and the travel cost.