The Indianapolis Motor Speedway saw a different kind of race car take to the track this past weekend.
University of Waterloo students Brian Mao and Ben Zhang were part of a team that competed in the Indy Autonomous Challenge on Saturday for a top prize of $1 million US.
The challenge was to advance and push autonomous vehicle technology to the next level.
“And what better way to do that than to push the limits and drive at speeds much faster than any regular car,” Mao told CBC News from the Indianapolis Motor Speedway in an interview before Saturday’s race.
“That would force control design or path-finder algorithms to be that much more robust, that much more accurate and that much more competitively efficient.”
Mao and Zhang teamed up with students from schools like the Massachusetts Institute of Technology, the University of Pittsburgh and the Rochester Institute of Technology.
There were eight other teams from around the globe taking part in the race, each tasked with modifying a Dallara AV-21 race car. For the most part, the hardware was the same in each team’s car.
“We make minor tweaks on where to place the ethernet cables and what hardware we decide to use as the interface between the computer and the car,” explained Zhang, who is a master’s student in electrical and computer engineering.
“What distinguishes each team is the software stack that’s running behind the car, what algorithms are you using for each part that’s required to achieve a fully autonomous vehicle,” added Mao, a master’s student in applied mathematics.
Zhang said the driver’s seat was replaced with a computer system that is made up of different sensors and radars and cameras to allow the vehicle to drive by itself.
The price tag on Zhang’s and Mao’s team race car was about $1 million US, and it had the ability to reach top speeds of 200 km/h.
The competition was fierce. Zhang said other teams have dedicated research labs for this project, not to mention more time.
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But Zhang and Mao said a great asset to their team is the diversity of engineering, computer and mathematics background.
“We have all sorts of different ideas that could blend together,” Mao said. “The diversity is what distinguishes us.”
Mao and Zhang said after pouring many hours working and practising with a simulator into this race, actually setting foot on the Indianapolis Motor Speedway felt “amazing.”
“Seeing the real thing, in person, is completely different. This arena is huge. The videos do not do it justice,” Mao said.
“It’s such a fulfilling experience seeing a physical car drive around in front of your own eyes rather than just a bunch of pixels on a simulation.”
Mao told CBC K-W on Monday that their car was unable to finish the race due to a GPS issue.
“Unfortunately, our team crashed into a wall toward the end of the first lap resulting in a 7th place overall finish,” he said in an email. “There were a mix of emotions within the team, but we’ve definitely learned a lot from this. I’m sure that our team will come out stronger in the future.”
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The TUM Autonomous Motorsport from the Technical University of Munich won the challenge on Saturday and claimed the grand prize after their car did the two-lap race at an average speed of 219 km/h.
Zhang said he plans on taking a short break before he tackles other projects they have in the works. Mao said he is hoping to pursue a career in autonomous vehicles.