The preference of onboard activities in a new age of automated driving.

According to the economic theory assumption, travelers tend to monetize travel time based on factors related to their individual and trip characteristics. In the literature, a limited number of studies evaluating onboard activities on traveler's utility in the presence of the autonomous vehicle (AV) are found. In the current research, traveler preferences on board of three transport modes: individual-ride autonomous vehicle (IR-AV), shared-ride autonomous vehicle (SAV), and public transport (PT) are studied. The focus of this paper is the examination of travelers in urban areas, where traveling is relatively short, and the study of the travelers' main trip purposes. The impact of travel time, travel cost, and main onboard activity is estimated based on a discrete choice experiment (DCE). The in-vehicle onboard activities are divided into six onboard activities, where active and passive activities are considered. An experimental design and a stated preference (SP) survey are carried out. The result of the SP survey is analyzed, where a Mixed Logit (ML) model, which includes various explanatory variables, is applied. The developed model contains such variables as trip time, trip cost, main onboard activity, frequent transport mode, job, age, and car ownership. These variables show various effects on the probability of choosing a transport mode. The impact of change in travel time, travel cost, and each of the six onboard activities on traveler preferences is highlighted. As a result, variations on the impact of time, cost, and onboard activities are demonstrated. Furthermore, it is presented that people prefer using IR-AV over SAV and PT, while the probability of choosing SAV is the lowest. Besides, reading and using social media affect the utility of travelers positively (i.e., higher probability) to a greater extent than other activities, while writing alone demonstrates negative utility.