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How many Parking Spots will be Needed with Autonomous Vehicles? New research by Senseable City Lab at MIT and Allianz Quantifies Potential for Unprecedented Reduction

Cambridge, MA/ Singapore, 27th August 2018 -- Researchers at the Singapore - MIT Alliance for Research and Technology (SMART) and MIT Senseable City Lab (SCL), together with SCL’s collaborator Allianz – the global financial services firm, are studying the impact of Autonomous Vehicles (AVs) on urban mobility. Results from a new project, called Unparking, preliminarily show that it’s possible to achieve a reduction of more than 70% of parking needs. Current research focuses on Singapore, although the methodology could be applied to cities across the globe.

The Unparking project is being carried out as part of a multi-year collaboration with Allianz, one of the world’s leading insurers and asset managers, on the impact of AVs in cities. In particular, the work seeks to explore the future of mobility by looking at ways to reduce traffic, alleviate commuting times and increase efficiency. As collaborators, Allianz and the MIT Senseable City Lab are addressing a number of urban mobility issues that include shared mobility, parking reduction, traffic optimization, and their impact on urban health, happiness, and efficiency.

Raymond Au, Allianz Asia, Head of Asia Lab, said, “Our Allianz data science team in Singapore is delighted to bring industry expertise to support MIT’s academic and research work. City traffic, for example, is a burden we could all live without, and this collaboration is one step on the journey to improving congestion in cities globally. In fact, we’re confident that this partnership builds on our longstanding commitment to support and accelerate innovation in emerging fields and technologies in the smart cities of the future.”

Unparking proposes to estimate parking needs when AVs hit the road. Private cars sit idle 95% of the time and on average utilize at least two parking spots – one at home and another at work. In preliminary results deposited in research archive - ArXiv, researchers examine parking needs within four scenarios: private cars occupying at least two parking spaces; private cars sharing parking spaces; shared mobility and shared parking; as well as AVs and shared parking spaces.

In short, the gradual transition to AVs will bring substantial decreases in the number of cars and parking required by them. “Self-driving vehicles can have huge implications for urban traffic”, said Dr. Daniel Kondor, Project Lead and a Postdoctoral researcher at SMART. Carlo Ratti, Professor of the Practice and Director of the Senseable City Lab at MIT and Principal Investigator at SMART, added: “Self-driving vehicles will bridge the gap between private and public modes of transportation. Rather than sitting idle in a parking spot all day, autonomous vehicles could bring you to work in the morning and then assist someone else in your family, neighborhood, social community, or city.”

Agent-based simulation based on parameters

The research uses an agent-based simulation of mobility in Singapore, involving over 600,000 commuters driving cars and a baseline estimate of 1.37 million parking spots. Preliminary results indicate that a fleet of 200,000 cars could serve all trips by replacing private vehicles with shared AVs, without any extra delay incurred on passengers. The AVs would only require 410,000 parking spaces. Optimizing the solutions for smaller fleet sizes indicate that even higher reductions are possible, but they would require empty AVs traveling more between one trip and the next one: a fleet size as small as 90,000 would be possible, requiring only 210,000 parking spaces, but would result in 20% more total distance traveled, meaning more cars on the road. These latter numbers would mean an 85% reduction in both the number of vehicles and parking spaces used. These findings are based on these parameters:

(1) All AVs are shared; and no ride-sharing is involved;
(2) Waiting time for passengers are not taken into account.

Paolo Santi, Research Scientist at MIT Senseable City Lab, commented: “The framework used in our study can also be applied to promote the potential benefits of reduced parking needs and traffic in the city.”

The Unparking analysis is currently being extended to other cities. Research was carried out at the MIT Senseable City Lab in Cambridge, MA, USA and at SMART, in Singapore. Allianz is a member of the Senseable City Consortium. This research was funded by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.

Find out more about the research here.


The Senseable City Lab at the Massachusetts Institute of Technology is a transdisciplinary research group that studies the interface between cities, people and technologies. Not bound by the methodologies of a single field, the Lab is characterized by an omni-disciplinary approach, and speaks the language of designers, planners, engineers, physicists, biologists and social scientists. Senseable is as fluent with industry partners as it is with metropolitan governments, individual citizens and disadvantaged communities. Through design and science, the Lab develops and deploys tools to learn about cities—so that cities can learn about us.


Singapore-MIT Alliance for Research and Technology (SMART) is a major research enterprise established by the Massachusetts Institute of Technology (MIT) in partnership with the National Research Foundation of Singapore (NRF) since 2007. SMART is the first entity in the Campus for Research Excellence and Technological Enterprise (CREATE) developed by NRF. SMART serves as an intellectual hub for research interactions between MIT and Singapore. Cutting-edge research projects in areas of interest to both Singapore and MIT are undertaken at SMART. SMART comprises an Innovation Centre and five Interdisciplinary Research Groups (IRGs): Antimicrobial Resistance (AMR), BioSystems and Micromechanics (BioSyM), Disruptive Technology for Agricultural Precision (DiSTAP), Future Urban Mobility (FM) and Low Energy Electronic Systems (LEES).