Evaluating Automated Demand Responsive Transit Using Microsimulation

Recent advancements in automated vehicle technology and the concurrent emergence of ride-hailing services have focused increasing attention on Automated Mobility-on-Demand (AMOD; a system of shared driverless taxis) as a potential solution for sustainable future urban mobility. However, the impacts of an unrestricted deployment of AMOD are as yet uncertain and likely to be context-specific; evidence with existing on-demand services suggests that they may lead to the cannibalization of mass-transit and increased traffic congestion. In this context, automated demand-responsive transit (also termed microtransit), which provides similar on-demand services (stop-to-stop or curbside) through higher capacity vehicles, may prove to be a promising substitute and/or complement. In this study, we evaluate the performance of such an automated demand response transit system (hereafter AMOD minibus) through agent-based simulations of the Singapore network. Towards this end, we extend SimMobility (an agent- and activity-based microsimulation laboratory) with the capability of modeling an AMOD minibus service including demand, supply and their interactions. On the demand side, we use an activity-based model system that draws on data from a stated-preferences survey conducted in Singapore. On the supply side, an insertion heuristic is applied to dynamically perform both the assignment of requests to vehicles and vehicle routing. Scenario simulations on the Singapore network (with an area-wide deployment of the AMOD services) indicate the potential benefits of an automated demand responsive transit service for local circulation, which can result in a reduction of Vehicle Kilometres Traveled of up to 50% (compared to the AMOD shared taxis) whilst satisfying the same demand, with a modest increase in average travel times.