The Official Vehicle that all Indy Autonomous Challenge Teams must use is the Dallara-produced AV-21 that has been retrofitted with hardware and controls to enable automation.
Image: Indy Autonomous Challenge/Cisco

The Indianapolis Motor Speedway will host the first autonomous racecar competition on October 23 with algorithms driving the cars instead of humans. College students are writing the software to power the cars.

There are 10 teams representing 21 universities competing in the Indy Autonomous Challenge:

  • AI Racing Tech – University of Hawai’i, University of California San Diego
  • Autonomous Tiger Racing – Auburn University
  • Black & Gold Autonomous Racing – Purdue University, United States Military Academy at West Point
  • Cavalier Autonomous Racing – University of Virginia
  • EuroRacing – University of Modena and Reggio Emilia (Italy), University of Pisa (Italy), ETH Zürich (Switzerland), Polish Academy of Sciences (Poland)
  • IUPUI-IITKGP-USB – Indiana University-Purdue University Indianapolis, Indian Institute of Technology Kharagpur (India), Universidad de San Buenaventura (Colombia)
  • KAIST – Korea Advanced Institute of Science and Technology (South Korea)
  • MIT-PITT-RW – Massachusetts Institute of Technology, University of Pittsburgh, Rochester Institute of Technology, University of Waterloo (Canada)
  • PoliMOVE – Politecnico di Milano (Italy), University of Alabama
  • TUM Autonomous Motorsport – Technische Universität München (Germany)

The first team to cross the finish line in 25 minutes or less will win $1 million. Second place is $250,000 and third place is $50,000. The remaining prize money was awarded earlier in the competition for the first and second place finishers in a simulated race.

SEE: 5 Internet of Things (IoT) innovations (free PDF) (TechRepublic)

Teams will use a Dallara AV-21 designed for autonomous racing. Clemson University’s Deep Orange 12 team re-engineered and assembled the vehicle to incorporate automation. According to a press release, this allows the racecar to use each team’s driverless algorithms which will perform all the driving tasks. The student teams wrote the autonomous driving software which makes driving decisions based on information from cameras, GPS inputs and sensors. Long-range LiDAR provides high resolution, a wide horizontal field of view and dynamic scanning capabilities that allows the race car to recognize other cars and debris on the track.

Cisco is sponsoring the event and providing wireless connectivity to connect cars on the racetrack with drivers on the sidelines. This includes race control commands, telemetry data offload and GPS timing alignment. The connectivity infrastructure includes Cisco ultra-reliable wireless backhaul for private mobile connectivity and Cisco Catalyst industrial Switches which provide up to 40 Gigabit throughput in the vehicle to connect the sensors in the car. The switches provide the necessary bandwidth and network speed to process information during a race, according to Cisco.

Autonomous vehicles and Clemson University

Clemson’s Deep Orange 12 team has been working on the autonomous vehicle for about two years. The team spent about 18 months designing the self-driving car, according to the University. The students had to build an autonomous vehicle that “had to operate at high speeds, follow complicated race control procedures and fit into a tightly-constrained, aerodynamic package,” according to a blog post from the University. The 40-student team unveiled their finished car in Indianapolis in May.

The Deep Orange project is a long-standing program at the university that connects students with industry experts to design a prototype. The two-year master’s degree program for automotive engineering students provides hands-on experience in vehicle design, engineering, prototyping and production. With this autonomous project, the students worked with more than 38 suppliers, partners and organizations to develop new engineering solutions, components and software.

The car’s feature set includes:

  • Advanced perception systems
  • Precision high-speed drive-by-wire control
  • Low-latency, high-throughput, ultra-reliable V2X communication
  • Purpose-built structural racing engine
  • High-speed on-board computing and software
  • A design that allows for series production
  • Rules and procedures for head-to-head autonomous racing
  • Ultra-compact aerodynamic component packaging

Robert Prucka, Deep Orange 12 faculty lead and an associate professor with the Clemson University Department of Automotive Engineering, said in the blog post that the demands of this project went far beyond previous Deep Orange projects, “not just in the technology itself but with the short timeline, series production, disparate systems and staying safe during COVID.”