Autonomous Mobility On-Demand (AMoD) Systems and their Potential Impacts on Mode Choice and Weekly Activity Patterns: A Case Study in Singapore

Abstract

The use of on-demand ride services continues to grow rapidly in recent years. At some point, given current technologies of automation, it is plausible that these rides will be driverless. This research examines the following questions: are people eager to adopt autonomous mobility on-demand (AMoD) ride services and will they shift their travel behaviors and activity patterns as a response to these services? In this paper, we leverage a rich and one-of-a kind week-long data set from a context-aware stated preference survey collected through the mobile phone application called Future Mobility Sensing (FMS) and estimate an ordered logit model to answer these questions. Our key findings suggest that people would like to try AMoD, but they are not willing to completely or significantly shift to the new alternative mode. Moreover, those who are likely to try AMoD tend to be car-less, young, and frequent users of ride-hailing services. They would use AMoD to perform additional leisure, personal, and meal activities, most preferably in the morning.