Demand Exploration of Automated Mobility On-Demand Services Using an Innovative Simulation Tool

Abstract

The prospect of automated mobility on-demand (AMoD) services in urban areas has highlighted critical challenges surrounding the sustainable development of urban mobility. To address this gap, we created an improved simulation tool by combining SimMobility’s demand simulator with the hybrid meso-micro supply model of Aimsun Next. A realistic and city-scale examination of AMoD using such an advanced simulation tool can address the limitations identified in the literature and significantly promote the understanding of AMoD services. In this paper, we demonstrate the use of our improved simulation tool and focus on demand exploration of AMoD services in the Tel-Aviv metropolitan area. We employ an activity- and agent-based framework, for both single and shared AMoD rides, and explore 6 service cost scenarios and its impact on demand elasticities, mode choice, travel patterns and AMoD use by population groups. Our results indicate that there is no existing latent demand in Tel-Aviv metropolitan area and the extent of mode shifts from active modes and public transportation to AMoD is neglectable. This is due to AMoD services average travel costs, which is high as compared to all other modes, even with the largest fare reduction examined. Furthermore, it was found that AMoD demand, as a single service, is more elastic than when AMoD is shared, as cost elasticities drops as fare reduction increases. Unlike other modes of transportation, the maximum number of AMoD trips is obtained for trips between 10 to 20 kilometers, while young riders and full-time students are responsible for most of AMoD trips.

Keywords

• Automated mobility-on-demand
• agent-based simulation
• scenarios
• simmobility
• aimsun