Episode 0027: Madhur Behl
Episode 27: Madhur Behl
In this thrilling episode of DRIVEN, Paul Perrone sits down with Madhur Behl, computer science professor at the University of Virginia and an expert in autonomous racing technology, to explore the cutting-edge world of high-speed self-driving race cars. Discover how artificial intelligence and engineering brilliance combine to control vehicles moving at nearly 200 mph, all without a human driver behind the wheel. Madhur dives deep into the technical aspects of autonomous racing, sharing insights from his Cavalier Racing activities and offering a rare glimpse into the future of motorsports. Whether you're a tech enthusiast or a racing fan, this episode will leave you on the edge of your seat.
Key Topics Discussed:
- How steering, braking, and throttle systems are implemented in autonomous vehicles
- The role of advanced sensors like LiDAR and radar in high-speed racing
- Localization and path planning at racing speeds
- Obstacle detection and avoidance techniques in autonomous racing
- Computing power and real-time processing for high-speed decision-making
- Safety systems and fail-safes for vehicles traveling at nearly 200 mph
- The future of autonomous racing and the challenges ahead
Join us for an exhilarating ride into the fast-paced world of autonomous vehicle racing!
Additional Reading and Information:
- J. Chrosniak, J. Ning and M. Behl, "Deep Dynamics: Vehicle Dynamics Modeling With a Physics-Constrained Neural Network for Autonomous Racing," in IEEE Robotics and Automation Letters, vol. 9, no. 6, pp. 5292-5297, June 2024. https://ieeexplore.ieee.org/abstract/document/10499707
-T. Weiss and M. Behl, "This is the Way: Differential Bayesian Filtering for Agile Trajectory Synthesis," in IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10414-10421, Oct. 2022, https://ieeexplore.ieee.org/abstract/document/9839552
- World record lap at IMS: https://youtu.be/Kgh5gMFhFYE
