‘Human Vs. Autonomous Car’ Race Ends Before It Begins
A demonstration “race” between a (human) F1 race car driver Daniil Kvyat and an autonomous vehicle was just staged by the Abu Dhabi Autonomous Racing League.
Describing the league and the “man vs. machine” showdown, Ars Technica writes, “Say goodbye to the human driver and hello to 95 kilograms of computers and a whole suite of sensors.”
But again, racing is hard, and replacing humans doesn’t change that. The people who run and participate in A2RL are aware of this, and while many organizations have made it a sport of overselling AI, A2RL is up-front about the limitations of the current state of the technology. One example of the technology’s current shortcomings: The vehicles can’t swerve back and forth to warm up the tires. Giovanni Pau, Team Principal of TII Racing, stated during a press briefing regarding the AI system built for racing, “We don’t have human intuition. So basically, that is one of the main challenges to drive this type of car. It’s impossible today to do a correct grip estimation. A thing my friend Daniil (Kvyat) can do in a nanosecond….”
Technology Innovation Institute (TII) develops the hardware and software stack for all the vehicles. Hardware-wise, the eight teams receive the same technology. When it comes to software, the teams need to build out their own system on TII’s software stack to get the vehicles to navigate the tracks. In April, four teams raced on the track in Abu Dhabi. As we’ve noted before, how the vehicles navigate the tracks and world around them isn’t actually AI. It’s programmed responses to an environment; these vehicles are not learning on their own. Frankly, most of what is called “AI” in the real world is also not AI.
Vehicles driven by the systems still need years of research to come close to the effectiveness of a human beyond the wheel. Kvyat has been working with A2RL since the beginning. In that time, the former F1 driver has been helping engineers understand how to bring the vehicle closer to their limit. The speed continues to increase as the development progresses. Initially, the vehicles were three to five minutes slower than Kvyat around a lap; now, they are about eight seconds behind. That’s a lifetime in a real human-to-human race, but an impressive amount of development for vehicles with 90 kg of computer hardware crammed into the cockpit of a super formula car. Currently, the vehicles are capable of recreating 90-95 percent of the speed of a human driver, according to Pau. Those capabilities are reduced when a human driver is also on the track, particularly for safety reasons….
The “race” was to be held ahead of the season finale of the Super Formula season… The A2RL vehicle took off approximately 22 seconds ahead of Kvyat, but the race ended before the practice lap was completed. Cameras missed the event, but the A2RL car lost traction and ended up tail-first into a wall…
Khurram Hassan, commercial director of A2RL, told Ars that the cold tires on the cold track caused a loss of traction.
Read more of this story at Slashdot.
A demonstration “race” between a (human) F1 race car driver Daniil Kvyat and an autonomous vehicle was just staged by the Abu Dhabi Autonomous Racing League.
Describing the league and the “man vs. machine” showdown, Ars Technica writes, “Say goodbye to the human driver and hello to 95 kilograms of computers and a whole suite of sensors.”
But again, racing is hard, and replacing humans doesn’t change that. The people who run and participate in A2RL are aware of this, and while many organizations have made it a sport of overselling AI, A2RL is up-front about the limitations of the current state of the technology. One example of the technology’s current shortcomings: The vehicles can’t swerve back and forth to warm up the tires. Giovanni Pau, Team Principal of TII Racing, stated during a press briefing regarding the AI system built for racing, “We don’t have human intuition. So basically, that is one of the main challenges to drive this type of car. It’s impossible today to do a correct grip estimation. A thing my friend Daniil (Kvyat) can do in a nanosecond….”
Technology Innovation Institute (TII) develops the hardware and software stack for all the vehicles. Hardware-wise, the eight teams receive the same technology. When it comes to software, the teams need to build out their own system on TII’s software stack to get the vehicles to navigate the tracks. In April, four teams raced on the track in Abu Dhabi. As we’ve noted before, how the vehicles navigate the tracks and world around them isn’t actually AI. It’s programmed responses to an environment; these vehicles are not learning on their own. Frankly, most of what is called “AI” in the real world is also not AI.
Vehicles driven by the systems still need years of research to come close to the effectiveness of a human beyond the wheel. Kvyat has been working with A2RL since the beginning. In that time, the former F1 driver has been helping engineers understand how to bring the vehicle closer to their limit. The speed continues to increase as the development progresses. Initially, the vehicles were three to five minutes slower than Kvyat around a lap; now, they are about eight seconds behind. That’s a lifetime in a real human-to-human race, but an impressive amount of development for vehicles with 90 kg of computer hardware crammed into the cockpit of a super formula car. Currently, the vehicles are capable of recreating 90-95 percent of the speed of a human driver, according to Pau. Those capabilities are reduced when a human driver is also on the track, particularly for safety reasons….
The “race” was to be held ahead of the season finale of the Super Formula season… The A2RL vehicle took off approximately 22 seconds ahead of Kvyat, but the race ended before the practice lap was completed. Cameras missed the event, but the A2RL car lost traction and ended up tail-first into a wall…
Khurram Hassan, commercial director of A2RL, told Ars that the cold tires on the cold track caused a loss of traction.
Read more of this story at Slashdot.