MIT & Stanford Help Ford Improve Automated Driving

Ford has sought the help of Massachusetts Institute of Technology and Stanford University for new automated driving research projects. Last month, Ford had unveiled the Ford Fusion hybrid research vehicle as a part of its ‘Blueprint for Mobility’ initiative which plans to bring autonomous functionality in vehicles by 2025. The Ford Fusion research vehicle uses four LiDAR sensors to generate a real-time 3D map of the surroundings by which it is able to detect obstacles and avoid them. MIT has been assigned the work of improving this system. The team from MIT uses advanced algorithms to help the vehicle predict future movement of other vehicles and pedestrians. This will help the vehicle plan a path around obstacles beforehand.

Ford 1
Ford 2 Ford 3

The problem with LiDAR sensors is that they cannot see through obstacles. So Stanford University has been assigned the task of modifying the sensors so that they can “take a peek around” obstacles and take evasive actions in case of an emergency. For example, if a truck is ahead of the automated vehicle it can peek ahead the truck and have a look at the obstacles ahead of the truck and if the truck brakes suddenly, the automated car will be able to change lanes safely avoiding oncoming traffic.

If you wish to know more about LiDAR sensors we would recommend you to take a look at the video below which shows how these sensors work on the US autonomous military machine TerraMax when it goes in a race with a 2013 Range Rover which is being driven by BBC Top Gear presenter James May .

Source: #-Link-Snipped-#


  • Sarathkumar Chandrasekaran
    Sarathkumar Chandrasekaran
    Good article @#-Link-Snipped-#
    .Stunning concept on peaking ahead of front going vehicle.So all giants racing for next gen autonomous cars, Fords initiative looks impressive but Who is going to be the first to launch it live?
  • Anoop Mathew
    Anoop Mathew
    On first looks it looked like a Tesla electric car to me!

    P.S.: That Terramax vs RR video is 👍

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