Impacts of Automated Mobility-on-Demand on traffic dynamics , energy and emissions: A case study of Singapore

Technological advancements have focused increasing attention on Automated Mobility-on Demand (AMOD) as a promising solution that may improve future urban mobility. During the last decade, extensive research has been conducted on the design and evaluation of AMOD systems using simulation models. This paper adds to this growing body of literature by investigating the network impacts of AMOD through high-fidelity activity-and agent based traffic simulation, including detailed models of AMOD fleet operations. Through scenario simulations of the entire island of Singapore, we explore network traffic dynamics by employing the concept of the Macroscopic Fundamental Diagram (MFD). Taking into account the spatial variability of density, we are able to capture the hysteresis loops, which inevitably form in a network of this size. Model estimation results at both the vehicle and passenger flow level are documented. Environmental impacts including energy and emissions are also discussed. Findings from the case study of Singapore suggest that the introduction of AMOD may bring about significant impacts on network performance in terms of increased VKT, additional travel delay and energy consumption, while reducing vehicle emissions, with respect to the baseline. Despite the increase in network congestion, production of passenger flows remains relatively unchanged.

Automated summary

This paper investigates the network impacts of AMOD through high-fidelity traffic simulation, exploring traffic dynamics and environmental impacts in the case study of Singapore. The findings suggest that the introduction of AMOD may bring about significant impacts on network performance, including increased VKT, additional travel delay, and energy consumption, while reducing vehicle emissions. Despite the increase in network congestion, production of passenger flows remains relatively unchanged.