))
Future Imperfect – Teddy Ort, Graduate Student, MIT Computer Science & Artificial Intelligence Lab (CSAIL) – Self-DrivingCars: Are We There Yet?
Archived series ("Inactive feed" status)
When?
This feed was archived on July 27, 2018 01:29 (
Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 209697012 series 2352213
Content provided by Richard Jacobs. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard Jacobs or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Globally, there are approximately 3000 motor vehicle deaths per day, 90% of which are due to human error such as distracted driving or impaired driving (drugs, alcohol, sleep deprivation). With statistics like these, it’s no wonder that auto manufacturers are in a race against time, and each other, to develop self-driving cars that will meet the challenges of all driving conditions.
Teddy Ort, a researcher and graduate student at MIT’s Computer Science & Artificial Intelligence Lab (CSAIL) a part of the Distributed Robotics Laboratory provides an interesting look at the future of self-driving vehicles. The MIT researcher discusses his research program’s goal of developing the algorithm and artificial intelligence (AI) necessary to enable a car to avoid all motor vehicle accidents.
We’ll learn why self-driving cars are not available to the public quite yet. While AI may be perfectly successful within a well-established grid such as a city, it may not score as well in rural areas that are not as delineated through mapping technology. Mr. Ort provides an overview of some of the technical issues that must be overcome before self-driving vehicles rule the roads. Though it may seem sensible that these cars simply do the driving when the tech is able, then hand over the control to a human when needed, data suggests this ‘passing of the reigns’ is a sticky problem indeed.
The MIT researcher gives an overview of the impediments to rural driving for these self-drivers, and how laser-scanning technology will provide the data necessary to read roads in much the same way a human would. And with unmarked roads comprising approximately 60% of all roads in the US, it’s easy to see why camera and laser scanning technology will have to rise to the challenges of rural driving.
Further, AI based technology will still have a learning curve when it comes to weather and reflective surfaces, for as a human can easily decipher that a car’s image seen in a rainy road reflection is not real, AI must learn this skill. Though challenges certainly lie ahead, Teddy Ort informs us that these self-driving cars are on their way to our garages, but exactly when that day will be remains unknown.
Podcast: Play in new window | Download | Embed | Listen, Subscribe & Review on iTunes
505 episodes
Share
