Network impacts of autonomous shared mobility

Disruptive transport technologies are introducing new opportunities for providing travelers and consumers with more options to meet their travel needs. These prospects are being facilitated by the convergence of a number of disruptive technologies including autonomous driving and mobile computing, and the shared (collaborative) economy. Although some of these disruptions are still a few years away (e.g. autonomous vehicles), they have already started to shape a vision for a very different future. Shared networks of autonomous vehicles, in particular, are already perceived as holding great promise for addressing the urban mobility challenges in our cities. This paper presents results from a simulation-based study which aimed to demonstrate the feasibility of using agent-based simulation tools to model the impacts of shared autonomous vehicles. A base case scenario representing the current situation (i.e. using traditional privately owned vehicles) and future scenarios of autonomous mobility on-demand (AMoD) were simulated on a real transport network in Melbourne, Australia. In addition to assessing the mobility impacts of AMoD, the paper also presents an assessment of how mode choice preferences impact the operation of fleets of autonomous vehicles. The results showed that using an AMoD system resulted in a significant reduction in both the number of vehicles required to meet the transport needs of the community (reductions between 43% and 88%), and the required on-street parking space (reductions between 57% and 83%. Investigations of shared mode choice preferences (car-share versus ride-share) also showed that shifting 40% of travelers to autonomous on-demand ride-sharing has the potential to deliver a 70% reduction in the total vehicle fleet size and 14% reduction in the total vehicle-kilometers-travelled compared to the Base Case Scenario.