It's On! AI Racing Tech Revs Up for 1st AV-24 Race
The AI Racing Tech team, led by the University of California, Berkeley, in partnership with the University of California, San Diego, and Carnegie Mellon University, is readying its considerable training and talent to compete in the first-ever head-to-head race of the new AV-24s – the world’s fastest autonomous racecars – at the Indy Autonomous Challenge (IAC) 2024.
Ten international, multi-university teams will take to the oval at the famed Indianapolis Motor Speedway in Indianapolis, Indiana – the racing capital of the world – on Friday, September 6, 2024. Tickets are available on the Indianapolis Motor Speedway website, and the event will be live-streamed for those who cannot attend in person.
The race will attract thousands of attendees from government, industry, and academia including 2,000 high school students studying Science, Technology, Engineering, and Math (STEM), according to the Indy Autonomous Challenge announcement of the upcoming event, which will also feature interactive exhibits and sessions on the future of mobility.
The UC Berkeley-led AI Racing team is currently undergoing testing on the Kentucky Motor Speedway track this month in preparation for the September 6 race. You can follow the team @AIRacingTech on social media channels X, Facebook, and LinkedIn.
May the best software win!
The AI Racing Tech Team
The AI Racing Tech Team, the most decorated U.S.-based team participating in the Indy Autonomous Challenge, pushes untested boundaries and drives research to ensure the highest caliber of safety for the future of commercial autonomy. Co-led by UC Berkeley Principal Investigator Allen Yang and AI Motorsports Race Principal Gary Passon, the team includes faculty and students from UC San Diego, Carnegie Mellon University, and the University of Hawai’i.
The UC Berkeley Robot Open Autonomous Racing (ROAR) program
The UC Berkeley Robot Open Autonomous Racing program (ROAR) was launched in 2019 to advance solutions of Autonomous Systems, Intelligent Machines, and Human-in-the-Loop Control for extreme robotics applications. Its faculty and students have extensive experience in developing high-performance algorithms for 3D Perception, Model Predictive Control, Reinforcement Learning, Generative AI, and Simulation and Virtual Reality, and have received major funding from NSF, ONR, ARL, DARPA, along with industry sponsors.