Toward a Systematic Approach to the Design and Evaluation of Automated Mobility-on-Demand Systems: A Case Study in Singapore

Abstract

The objective of this work is to provide analytical guidelines and financial justification for the design of shared-vehicle mobility-on-demand systems. Specifically, we consider the fundamental issue of determining the appropriate number of vehicles to field in the fleet, and estimate the financial benefits of several models of car sharing. As a case study, we consider replacing all modes of personal transportation in a city such as Singapore with a fleet of shared automated vehicles, able to drive themselves, e.g., to move to a customer's location. Using actual transportation data, our analysis suggests a shared-vehicle mobility solution can meet the personal mobility needs of the entire population with a fleet whose size is approximately 1/3 of the total number of passenger vehicles currently in operation.

Autonomous Mobility-on-Demand Systems for Future Urban Mobility

“…The results presented in this chapter build upon a number of previous works by the author and his collaborators, namely [13] for the lumped approach, [14,15,16,17] for the spatial queueing-theoretical framework and the distributed approach, and [13,18] for the case studies. The rest of this chapter is structured as follows.…”

“…This case study discusses an hypothetical deployment of an AMoD system to meet the personal mobility needs of the entire population of Singapore [18]. The study, which should be interpreted as a thought experiment to investigate the potential benefits of an AMoD solution, addresses three main dimensions: (i) minimum fleet size to ensure system stability (i.e., uniform boundedness of the number of outstanding customers), (ii) fleet size to provide acceptable quality of service at current customer demand levels, and (iii) financial estimates to assess economic feasibility.…”

“…Fig. 19.5 Case study of Singapore [18]. Left figure: Performance curve with 100 regions, showing the availability of vehicles vs. the size of the system for both average demand (2-3 pm) and peak demand (7-8 am).…”

“…From the fleet-sizing arguments of Section 19.3.2.2, one shared self-driving vehicle in System 2 can effectively serve the role of about four private, human-driven vehicles in System 1, which implies an estimate of 2.5 years for the average lifespan of a self-driving vehicle. Tallying the aforementioned costs on a fleet-wide scale and distributing the sum evenly among the entire Singapore population gives a COS 2 of $12,563/year (see [18] for further details about the cost breakdown). According to COS values, it is more affordable to access mobility in System 2 than System 1.…”

The autonomous car—a blessing or a curse for the future of low carbon mobility? An exploration of likely vs. desirable outcomes

“…Astonishingly, the average car in the US remains parked for 96 % of the time [52] and space used for car parking in CBDs (Central Business Districts) can take up to 80 % of CBD land area [53] highlighting the potential of this transformation. Additionally, it has been estimated that in Singapore for example, the total current mobility needs of the city can be accommodated by approximately 1/3 of the current passenger vehicle fleet if it was replaced with a fleet of shared autonomous vehicles [54]. Such a move would hugely impact congestion and may also introduce environmental benefits through eco-driving, reduced idling or platooning of AVs which improves fuel efficiency and reduces the average travel time [55].…”