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Driverless-vehicle options now include scooters

Self-driving scooter demonstrated at MIT complements autonomous golf carts and city cars.
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An autonomous mobility scooter and related software were designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).
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Caption: An autonomous mobility scooter and related software were designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).
Credits: Courtesy of the Autonomous Vehicle Team of the SMART Future of Urban Mobility Project
Before riding the scooter, users were asked how safe they considered autonomous vehicles to be, on a scale from one to five; after their rides, they were asked the same question again. Experience with the scooter brought the average safety score up, from 3.5 to 4.6.
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Caption: Before riding the scooter, users were asked how safe they considered autonomous vehicles to be, on a scale from one to five; after their rides, they were asked the same question again. Experience with the scooter brought the average safety score up, from 3.5 to 4.6.
Credits: Courtesy of the Autonomous Vehicle Team of the SMART Future of Urban Mobility Project

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An autonomous mobility scooter and related software were designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).
Caption:
An autonomous mobility scooter and related software were designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).
Credits:
Courtesy of the Autonomous Vehicle Team of the SMART Future of Urban Mobility Project
Before riding the scooter, users were asked how safe they considered autonomous vehicles to be, on a scale from one to five; after their rides, they were asked the same question again. Experience with the scooter brought the average safety score up, from 3.5 to 4.6.
Caption:
Before riding the scooter, users were asked how safe they considered autonomous vehicles to be, on a scale from one to five; after their rides, they were asked the same question again. Experience with the scooter brought the average safety score up, from 3.5 to 4.6.
Credits:
Courtesy of the Autonomous Vehicle Team of the SMART Future of Urban Mobility Project

At MIT’s 2016 Open House last spring, more than 100 visitors took rides on an autonomous mobility scooter in a trial of software designed by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART).

The researchers had previously used the same sensor configuration and software in trials of autonomous cars and golf carts, so the new trial completes the demonstration of a comprehensive autonomous mobility system. A mobility-impaired user could, in principle, use a scooter to get down the hall and through the lobby of an apartment building, take a golf cart across the building’s parking lot, and pick up an autonomous car on the public roads.

The new trial establishes that the researchers’ control algorithms work indoors as well as out. “We were testing them in tighter spaces,” says Scott Pendleton, a graduate student in mechanical engineering at the National University of Singapore (NUS) and a research fellow at SMART. “One of the spaces that we tested in was the Infinite Corridor of MIT, which is a very difficult localization problem, being a long corridor without very many distinctive features. You can lose your place along the corridor. But our algorithms proved to work very well in this new environment.”

The researchers’ system includes several layers of software: low-level control algorithms that enable a vehicle to respond immediately to changes in its environment, such as a pedestrian darting across its path; route-planning algorithms; localization algorithms that the vehicle uses to determine its location on a map; map-building algorithms that it uses to construct the map in the first place; a scheduling algorithm that allocates fleet resources; and an online booking system that allows users to schedule rides.

Uniformity

Using the same control algorithms for all types of vehicles — scooters, golf carts, and city cars — has several advantages. One is that it becomes much more practical to perform reliable analyses of the system’s overall performance.

“If you have a uniform system where all the algorithms are the same, the complexity is much lower than if you have a heterogeneous system where each vehicle does something different,” says Daniela Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT and one of the project’s leaders. “That’s useful for verifying that this multilayer complexity is correct.”

Furthermore, with software uniformity, information that one vehicle acquires can easily be transferred to another. Before the scooter was shipped to MIT, for instance, it was tested in Singapore, where it used maps that had been created by the autonomous golf cart.

Similarly, says Marcelo Ang, an associate professor of mechanical engineering at NUS who co-leads the project with Rus, in ongoing work the researchers are equipping their vehicles with machine-learning systems, so that interactions with the environment will improve the performance of their navigation and control algorithms. “Once you have a better driver, you can easily transplant that to another vehicle,” says Ang. “That’s the same across different platforms.”

Finally, software uniformity means that the scheduling algorithm has more flexibility in its allocation of system resources. If an autonomous golf cart isn’t available to take a user across a public park, a scooter could fill in; if a city car isn’t available for a short trip on back roads, a golf cart might be.

“I can see its usefulness in large indoor shopping malls and amusement parks to take [mobility-impaired] people from one spot to another,” says Dan Ding, an associate professor of rehabilitation science and technology at the University of Pittsburgh, about the system.

Changing perceptions

The scooter trial at MIT also demonstrated the ease with which the researchers could deploy their modular hardware and software system in a new context. “It’s extraordinary to me, because it’s a project that the team conducted in about two months,” Rus says. MIT’s Open House was at the end of April, and “the scooter didn’t exist on February 1st,” Rus says.

The researchers described the design of the scooter system and the results of the trial in a paper they presented last week at the IEEE International Conference on Intelligent Transportation Systems. Joining Rus, Pendleton, and Ang on the paper are You Hong Eng, who leads the SMART autonomous-vehicle project, and four other researchers from both NUS and SMART.

The paper also reports the results of a short user survey that the researchers conducted during the trial. Before riding the scooter, users were asked how safe they considered autonomous vehicles to be, on a scale from one to five; after their rides, they were asked the same question again. Experience with the scooter brought the average safety score up, from 3.5 to 4.6.

Press Mentions

Wired

In this Wired video, Prof. Daniela Rus speaks about how her research group is developing and applying autonomous vehicle technology to other vehicles, in particular wheelchairs. Rus explains that she envisions the technology “impacting anyone who is confined in their motions. I see it applied in hospitals, in retirement communities, in assisted living communities.”  

Quartz

MIT researchers have created a self-driving scooter that can be used both indoors and outdoors, reports Siyi Chen for Quartz. The scooter will “slow down or stop in order to calibrate a new route” when faced with an obstacle, explains Chen.

Reuters

Reuters reporter Yiming Woo highlights a new autonomous scooter developed by researchers from MIT, the National University of Singapore and the Singapore-MIT Alliance for Research and Technology (SMART). The scooter should be able to help “improve mobility for all ages, cut down on the need for cars and also lower accident rates.”

Digital Trends

MIT researchers have developed a software system that allows scooters, cars and golf carts to operate autonomously, writes Dyllan Furness of Digital Trends. Prof. Daniela Rus explains that the system works both indoors and outdoors and “provides an end-to-end solution starting with the home or hospital room all the way to the destination.”

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