Impacts of Autonomous Vehicles on Consumers Time-Use Patterns

Abstract

We use the American Time Use Survey (ATUS) to characterize how different consumers in the US might use Autonomous Vehicles (AVs). Our approach is to identify sub-groups of the population likely to benefit from AVs and compare their activity patterns with an otherwise similar group. The first subgroup is working individuals who drive to work with long total travel times. Auto-travelers in the top 20% of travel time number 19 million and travel 1.6 h more on a workday than those in the bottom 80%. For car-commuting professionals, the additional travel time of the long-traveling group comes from 30 min less work, 29 min less sleep, and 30 min less television watching per day. The second subgroup is working individuals with a long travel time and who take public transport. Long public transit riders show very similar differences in activity times as the driving subgroup. Work, sleep, and video functionalities of AVs are presumably in high demand by both groups. The third sub-group identified is elderly retired people. AVs enable mobility-restricted groups to travel more like those without restrictions. We compare two age groups, 60–75 years and >75 years old, the latter, on average, experiencing more mobility restrictions than their younger counterparts. The retired population older than 75 years numbers 16 million and travels 14 min less per day than retirees aged 60–75 years. The main activity change corresponding to this reduced travel is 7 min per day less shopping and 8 min per day less socializing. If older retired people use AVs to match the lifestyle of the 60–75 years old group, this would induce additional personal travel and retail sector demand. The economic, environmental and social implications of AV are very difficult to predict but expected to be transformative. The contribution of this work is that it utilizes time-use surveys to suggest how AV adoption could induce lifestyle changes inside and outside the vehicle.