Skip to main content

Driverless-vehicle options now include scooters

Researchers have developed an autonomous mobility scooter which 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.
November 9, 2016 Read time: 2 mins

Researchers have developed an autonomous mobility scooter which 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.

Developed 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 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. It also includes route-planning algorithms; localisation 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.

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.

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, of the 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.”

Software uniformity also means that the scheduling algorithm has more flexibility in its allocation of system resources.

“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.

The researchers described the design of the scooter system and the results of the trial in a paper they presented recently at the IEEE International Conference on Intelligent Transportation Systems in Rio de Janeiro, Brazil.

Related Content

  • June 4, 2015
    The future looks bright for ITS
    Professor Eric Sampson talks about the past successes of ITS, its potential for the future and the challenges the industry faces. If anybody should know when Intelligent Transport Systems started that person is Professor Eric Sampson, a visiting professor at both Newcastle and London City Universities. Having spent 40 years working for the UK’s Department of Transport and other public administrations, Professor Sampson now supports the European Commission on ITS systems and advises ERTICO ITS-Europe and ITS
  • August 2, 2013
    Suppliers reshape to provide tolling and traffic management expertise
    Jason Barnes examines the trend towards single source supply of complete tolling and traffic management solutions with some senior tolling industry figures. Only a few years back, the major tolling system suppliers were aggressively positioning themselves as one-stop shops for tolling solutions and operations. No sooner has that little flurry of innovation settled than another trend has emerged – tolling companies wanting to become major ITS suppliers as well. Various tolling company seniors have in recent
  • February 3, 2012
    Detection analysis technology successfully predicts traffic flows
    David Crawford investigates new detection analysis technology from IBM. Locations on both the East and West Coasts of the US are scheduled for early deployments of IBM's new Traffic Prediction Tool (TPT) statistical analysis model for the fine-time resolution and near-term prediction of road flow conditions. Developed by IBM's Watson Research Laboratories, TPT is designed to analyse data from the the key detection indicators - average vehicle volumes and speeds passing a location in a given time interval -
  • May 23, 2012
    Civil engineers find fuel savings where the rubber meets the road
    A new study by civil engineers at MIT shows that using stiffer pavements on America’s roads could reduce vehicle fuel consumption by as much as three per cent, that could add up to 273 million barrels of crude oil per year, or US$15.6 billion at today’s oil prices. This would result in an accompanying annual decrease in CO2 emissions of 46.5 million metric tons.