GST refunds for processing fees paid on Development Applications and Lodgments. Click for more details.
Be wary of phishing or scam attempts. URA will NOT ask for sensitive personal information relating to your accounts, such as your Singpass ID/password or your banking ID/password. As a safeguard, all official SMSes sent by URA will not carry clickable links. Use our feedback form to report any suspicious SMSes supposedly from URA. Stay vigilant and safe! Learn how to spot these scams.

Creating Future Cities with Self-Driving Vehicles

  Published: 26 November 2017
  Theme: Mobility

self-driving-cars-1
(Photo: Ministry of Transport, Singapore)

Self-driving vehicles (SDVs) are expected to transform cities and the lives of the people who live in them. From Lisbon to Singapore, cities around the world have begun to experiment with SDVs — both in theory and in small-scale practice on public roads. The experiments hint at the potential for urban planners to resolve congestion issues, create safer streets for pedestrians and cyclists, as well as achieve more efficient usage of urban land, all of which can be done by implementing SDVs in feasible ways — for example as electric-powered, shared-use fleets to fill first and last mile gaps.

With this in mind, further research needs to be done to finesse the optimal deployment of SDVs. “For urban planners, two key streams of research are how transportation patterns could change with SDVs, and how land use needs to be recalibrated,” says Professor Moshe Ben-Akiva, Director of the Massachusetts Institute of Technology (MIT) Intelligent Transport Systems Lab. Research has already dived into these streams — often with insightful results.

Maximising the Benefits of SDVs Through Shared-use

The first step is to examine how SDVs can best be deployed on the roads. If, like manually driven cars, a private ownership model were applied to SDVs instead of a shared-use model, existing issues of congestion would unlikely improve. To examine the impact of shared-use SDVs, researchers at the International Transport Forum (ITF) carried out a series of computer-based simulations on two different car-sharing concepts: TaxiBots — SDVs shared by several passengers at the same time (popularly known as ride-sharing) — and AutoVots — cars that take passengers one after another (car sharing) using the street network of the city of Lisbon, Portugal. 

In the various simulations, passenger trips were made with shared vehicles or a mix of shared vehicles and Lisbon’s high-capacity subway system. Simulation tests used two time periods: peak hours and the average of a 24-hour day. Both tests were based on a premise that no buses or private cars would ply the road. The researchers used origin and destination data derived from a fine-grained database of surveyed trips to replicate real-world commuter patterns and routes.

Based on these simulations, the researchers found that fleets of shared SDVs (TaxiBots) could deliver the same mobility with significantly fewer cars on the road. In the best simulated outcome, a city serviced by TaxiBots and a rapid inter-urban rail system removed 90 per cent of cars in the city over the course of a 24-hour day1 . The same combination of rail and TaxiBots removed 65 per cent of cars overall during peak hours.

 

self-driving-cars-3

Effects of ride-sharing SDVs used in conjunction with high-capacity public transport on urban roads in a 24-hour window. (Infographic taken from International Transport Forum video2)

Without taking into account other road vehicles, the ITF simulations have reduced external validity. Their results, however, are still noteworthy. The freeing up of roads with shared-use SDV fleets means that urban planners have the opportunity to reconfigure this freed capacity for greater public benefit.

Planning and Designing the City for SDVs

Focusing on the impact of SDV implementation within UK locales, including city centres, suburban spaces, motorways and rural areas, a white paper drafted by transport engineers WSP Parsons Brinckerhoff, in association with architect planner Farrells, echoes the Lisbon study. The authors note that under a shared-use model, far fewer SDVs than cars would be needed on the road to maintain travel patterns.

New city developments with a dedicated zone for shared SDV use could result in up to 20 per cent additional developable area, say the authors, due largely to the reduction in car parking spaces and the simplification of road space. With the reclaimed land parcels, urban planners could generate significant uplift in land value and well-being by greening these spaces and providing activity areas for pedestrians and cyclists. In land-scarce Singapore, driverless zones such as former car parks could be repurposed constructively with urban gardening and energy generation applications, in addition to public amenities.

 

self-driving-cars-2

Potential benefits of mass SDV implementation in London. (Infographics: Making Better Places: Autonomous vehicles and future opportunities)

A City’s Journey to a ‘Car-lite’ Society

The Singapore Government has been working with partners to trial SDVs since 20143. The scope of the trials has been broad, with multiple modes of SDVs tested. In 2016, NuTonomy — a team from MIT — partnered with local experts to execute the world’s first driverless taxi trials on public roads4. Trials for autonomous electric-powered buses by the Land Transport Authority, meanwhile, address the possibility of larger-capacity modes of SDVs in Singapore5. In early 2019, four mobility-on-demand vehicles, each with seating capacities ranging from 15 to 20 passengers, will be deployed in a pilot public trial6.

Autonomous vehicle

A driverless taxi on public road trials in Singapore. (Image: NuTonomy)

Once multiple modes of SDVs can be shown to function on public roads without a glitch, research should focus on how best to manage a shared fleet of SDVs and design the urban environment to facilitate its deployment. According to Prof Ben-Akiva, supply-side fleet optimisation strategies would need to be mapped out alongside demand-side passenger decision-modelling to measure the impact of SDVs on the built environment

Meanwhile, the impact and trade-offs of SDVs needs to be continuously examined. For example, SDVs should not eat into the use of non-motorised modes of transport. Singapore is developing a regulatory framework for SDVs that will address this and other critical issues.

Based on this research, urban planners can then proceed to design for integrated SDV-mass transit deployment. Freed up road space from smaller lane widths and headway, in particular, can be repurposed for uses such as greenery, pedestrian paths or SDV parking areas to reap positive externalities. "Supporting infrastructure such as drop-off pickup points, charging points for electric SDVs and maintenance facilities should also be factored into urban plans," says Mindy Ong, Planner, Urban Redevelopment Authority of Singapore.

Given the myriad factors at play, it is unlikely that mass SDV implementation in cities will be a seamless, one-off process. Through vigorous research, urban planners should work with transportation and technology stakeholders to plan for an optimal urban environment where, in the long run, SDVs can complement the way of life of city dwellers.

References:

  1. http://oecdinsights.org/2015/05/13/the-sharing-economy-how-shared-self-driving-cars-could-change-city-traffic/
  2. https://www.youtube.com/watch?v=j9kK0RHl-LI
  3. http://smart.mit.edu/images/pdf/news/2014/Driverless_Car_NR_270114_Final.pdf
  4. http://www.straitstimes.com/singapore/transport/worlds-first-driverless-taxi-trial-kicks-off-in-singapore
  5. https://www.lta.gov.sg/apps/news/page.aspx?c=2&id=62852bf0-c8d2-4e2a-a940-88faeaf8b696
  6. https://www.smartnation.sg/initiatives/Mobility/self-driving-vehicles-sdvs--future-of-mobility-in-singapore

 

Top