Abstract
Shared Autonomous Mobility on-Demand (AMoD) systems are prescribed by many as a solution to tackle congestion. In these systems, customers are serviced on demand by a fleet of shared Autonomous Vehicles (AV). The main aim of this novel mobility system is meeting travel aspirations of people while reducing the number of passenger cars on roads. Our study explores the relationship between fleet size and induced Vehicle-Kilometres Travelled (VKT) in AMoD systems in the context of a case study in Melbourne, Australia. To achieve this, an agent based simulation model was developed to investigate this relationship through scenario analysis. Our results show that fleets of on-demand shared AVs have the potential to reduce the number of vehicles by 79% on our roads. These systems, however, lead to 61% more VKT within the transport network. This finding indicates that the vast majority of literature is overoptimistic about the potential of AMoD systems for mitigating congestion. This paper also reports on an investigation into the effects of travel demand pattern on the performance of these systems, and shows that the impact of this phenomenon on their efficiency is not trivial. Further, our simulation results reveal a quadratic relationship between AMoD fleet size and induced VKT in the system, which holds for all travel demand patterns.
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Notes
- 1.
Note that the NTRR values in D1 and D2 are the same (0.56) for the area 34–53 (Fig. 4).
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Javanshour, F., Dia, H., Duncan, G. (2019). Exploring System Characteristics of Autonomous Mobility On-Demand Systems Under Varying Travel Demand Patterns. In: Mine, T., Fukuda, A., Ishida, S. (eds) Intelligent Transport Systems for Everyone’s Mobility. Springer, Singapore. https://doi.org/10.1007/978-981-13-7434-0_17
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