On-Road vs. Off-Road Self-Driving Car Research

Would you believe we're 90-95% of the way to solving the self-driving car challenge?! Researchers, like Srikanth Saripalli, are building and testing some of the most complex vehicles, sensor systems and algorithms that are enabling us to advance autonomous vehicle technology faster and faster.

Dr. Sri Saripalli is the Director of the Center for Autonomous Vehicles and Sensor Systems at Texas A&M University, where his research takes his team into both the on-road and off-road sides of self-driving cars. He has a gift for taking complex topics and making them accessible and fascinating for any listener.

3 Big Takeaways from this episode:

1. We're 90-95% of the way to having fully self-driving vehicles.
2. On-road and off-road vehicles present two completely different sets of challenges to researchers developing the algorithms to make them autonomous.
3. Common sense isn't so common - this uniquely human trait is difficult to put into an algorithm. But researchers are working on it, in a concept called generalized artificial intelligence.

Show Notes

What's so fascinating about self-driving cars?

There are countless applications for robotics and artificial intelligence, but nothing seems to catch the interest of people across the world like autonomous vehicles.

Driving is such an integral, common aspect to all our lives, so we're drawn to the technologies and concepts that could enable a computer to drive for us. This technology has the potential to change the world!

Texas A&M University

The work being done at Texas A&M University is fascinating. Find out what makes it unique - from the funding sources, to research timelines, to the variety of applications being researched.

On-Road vs. Off-Road Self-Driving Cars: What's the difference?

As it turns out...a lot.

On-road vehicles have a rule system in place to follow - street signs, roads, lines, and driving rules set by the Department of Transportation make writing algorithms simple...or do they? Pedestrians, obstacles, "the unknown" and the possibility of breaking the rules offers challenges to researchers.

Off-road vehicles may have more freedom from DOT rules, but they're faced with a complex set of obstacles to constantly feed through their algorithms and make decisions. This is the challenge Sri and his team face as they do research for the DoD.

Common Sense and Generalized AI

Of course we can't have a conversation about self-driving vehicles without bringing up artificial intelligence. Sri helps us understand what generalized artificial intelligence is, and why it presents such a challenge to researchers who develop AI algorithms.

More Resources

See more from Sri and his team: https://unmannedlab.github.io