A new self-driving truck — manufactured by Volvo and loaded with autonomous vehicle tech developed by Aurora Innovation — could be on public highways as early as this summer. The Volvo VNL Autonomous truck, which was revealed Monday evening at the ACT Expo in Las Vegas, is the product of a partnership between Aurora and […]
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Wander the pits at any professional motorsports event, especially something like Formula 1, and you’ll see endless computer displays full of telemetry. Modern teams are awash in real-time digital feedback from the cars. I’ve been in many of these pits over the years and marveled at the streams of data, but never have I seen an instance of the Microsoft Visual Studio software development suite running there right amid the chaos.
But then, I’ve never attended anything like the inaugural Abu Dhabi Autonomous Racing League event this past weekend. The A2RL, as it is known, is not the first autonomous racing series: There’s the Roborace series, which saw autonomous race cars setting fast lap times while dodging virtual obstacles, and the Indy Autonomous Challenge, which most recently ran at the Las Vegas Motor Speedway during CES 2024.
While the Roborace focuses on single-car time trials and the Indy Autonomous series centers on oval action, A2RL set out to break new ground in a couple of areas.
A2RL put four cars on track, competing simultaneously for the first time. And, perhaps more significantly, it pitted the top-performing autonomous car against a human being, former Formula 1 pilot Daniil Kvyat, who drove for various teams between 2014 and 2020.
The real challenge was behind the scenes, with teams staffed with an impressively diverse cadre of engineers, ranging from fledgling coders to doctorate students to full-time race engineers, all fighting to find the limit in a very new way.
Unlike Formula 1, where 10 manufacturers design, develop and produce completely bespoke cars (sometimes with the help of AI), the A2RL race cars are entirely standardized to provide a level playing field. The 550-horsepower machines, borrowed from the Japanese Super Formula Championship, are identical, and the teams are not allowed to change a single component.
That includes the sensor array, which features seven cameras, four radar sensors, three lidar sensors and GPS to boot — all of which are used to perceive the world around them. As I would learn while wandering the pits and chatting to the various teams, not everybody is fully tapping into the 15 terabytes of data each car hoovers up every single lap.
Some teams, like the Indianapolis-based Code19, only started work on the monumental project of creating a self-driving car a few months ago. “There’s four rookie teams here,” said Code19 co-founder Oliver Wells. “Everyone else has been competing in competitions just like this, some of them for up to seven years.”
Munich-based TUM and Milan-based Polimove have extensive experience running and winning in both Roborace and the Indy Autonomous Challenge. That experience carries over, as does the source code.
“On the one hand, the code is continuously developed and improved anyway,” said Simon Hoffmann, team principal at TUM. The team made adjustments to change the cornering behavior to suit the sharper turns in the road course and also adjust the overtaking aggression. “But in general, I would say we use the same base software,” he said.
Through the series of numerous qualifying rounds throughout the weekend, the teams with the greatest experience dominated the timing charts. TUM and Polimove were the only two teams to complete lap times in less than two minutes. Code19’s fastest lap, however, was just over three minutes; the other new teams were far slower.
This has created a competition that’s rarely seen in software development. While there have certainly been previous competitive coding challenges, like TopCoder or Google Kick Start, this is a very different sort of thing. Improvements in code mean faster lap times — and fewer crashes.
Kenna Edwards is a Code19 assistant race engineer and a student at Indiana University. She brought some previous app development experience to the table, but had to learn C++ to write the team’s antilock braking system. “It saved us at least a couple of times from crashing,” she said.
Unlike traditional coding problems that might require debuggers or other tools to monitor, improved algorithms here have tangible results. “A cool thing has been seeing the flat spots on the tire improve over the next session. Either they’ve reduced in size or in frequency,” Edwards said.
This implementation of theory not only makes for engaging engineering challenges but also opens up viable career paths. After earlier interning with Chip Ganassi Racing and General Motors, and thanks to her experience with Code19, Edwards starts full-time at GM Motorsports this summer.
That sort of development is a huge part of what A2RL is about. Shadowing the main on-track action is a secondary series of competitions for younger students and youth groups around the world. Before the main A2RL event, those groups competed with autonomous 1:8-scale model cars.
“The aim is, next year, we keep for the schools the smaller model cars, we’ll keep for the universities maybe doing it on go-karts, a bit bigger, they can play with the autonomous go-karts. And then, if you want to be in the big league, you start racing on these cars,” said Faisal Al Bannai, the secretary general of Abu Dhabi’s Advanced Technology Research Council, the ATRC. “I think by them seeing that path, I think you’ll encourage more guys to come into research, to come into science.”
It’s Al Bannai’s ATRC that’s footing the bill for the A2RL, covering everything from the cars to the hotels for the numerous teams, some of whom have been testing in Abu Dhabi for months. They also put on a world-class party for the main event, complete with concerts, drone races, and a ridiculous fireworks show.
The on-track action was a little less spectacular. The first attempt at a four-car autonomous race was aborted after one car spun, blocking the following cars. The second race, however, was far more exciting, featuring a pass for the lead when the University of Modena’s Unimore team car went wide. It was TUM that made the pass and won the race, taking home the lion’s share of the $2.25 million prize purse.
As for man vs. machine, Daniil Kvyat made quick work of the autonomous car, passing it not once but twice to huge cheers from the assembled crowd of more than 10,000 spectators who took advantage of free tickets to come see a little bit of history — plus around 600,000 more streaming the event.
The technical glitches were unfortunate. Still it was a remarkable event to witness and illustrated how far autonomy has come — and of course, how much more progress needs to be made. The fastest car was still upward of 10 seconds off of Kvyat’s time. However, it ran smooth, clean laps at an impressive speed. That’s in stark contrast to the first DARPA Grand Challenge in 2004, which saw every single competitor either crashing into a barrier or meandering off into the desert on an unplanned sojourn.
For A2RL, the real test will be whether it can evolve into a financially viable series. Advertising drives most motorsports, but here, there’s the added benefit of developing algorithms and technologies that manufacturers could reasonably apply in their cars.
ATRC’s Al Bannai told me that while the series organizers own the cars, the teams own the code and are free to license it: “What they compete on at the moment is the algorithm, the AI algorithm that makes this car do what it does. That belongs to each of the teams. It doesn’t belong to us.”
The real race, then, might not be on the track, but in securing partnerships with manufacturers. After all, what better way to inspire confidence in your autonomous technology than by showing it can handle traffic on the race track at 160 mph?
Hyundai has agreed to spend nearly $1 billion on Motional, an investment that will give the automaker a majority stake while providing the self-driving startup with the necessary capital to keep operating.
The Korean automaker invested $475 million directly into Motional as part of a broader deal that includes buying out joint venture partner Aptiv. As part of the deal, Hyundai will spend another $448 million to buy 11% of Aptiv’s common equity interest in Motional, according to information revealed Thursday in Aptiv’s first-quarter earnings report.
Aptiv also shared that it expects to reduce its common equity interest in Motional from 50% as of March 31 to about 15%, leaving Hyundai with the remaining 85% control. Aptiv Chairman and CEO Kevin Clark flagged in January that the company would reduce its ownership interest in Motional. The company said at the time that it would stop allocating capital towards Motional due to the high cost of commercializing a robotaxi business and the long road ahead to profits.
Aptiv on Thursday reduced its full-year net sales forecast for 2024 to be between $20.85 billion and $21.45 billion, down from between $21.3 billion to $21.9 billion.
Motional confirmed the new funding round and increased stake from Hyundai. The company did not respond to TechCrunch’s inquiry regarding the accuracy of Aptiv’s figures. Hyundai could also not be reached for confirmation.
Motional started as Boston-based autonomous vehicle startup nuTonomy in 2013, before being acquired by Delphi for $400 million. Delphi would later split it’s business with the Aptiv unit absorbing nuTonomy. The entity became Motional under a $4 billion Hyundai-Aptiv joint venture in 2019. While it’s clear from Aptiv’s earnings report that the company is trying to manage risks and optimize finances amid a less positive outlook, the company’s retreat, and Hyundai’s step forward, raises questions about Motional’s future.
In March, TechCrunch reported that Motional secured a bridge loan for an undisclosed amount as a lifeline while the AV startup secured its next round of longer-term funding. While it’s likely that this funding round from Hyundai fits that bill, Motional has not responded to TechCrunch’s request for more information about whether it will need to acquire more investors in the future.
Motional has been testing its autonomous vehicles with a safety driver behind the wheel in Boston, Pittsburgh, Las Vegas, Los Angeles and Singapore. The company’s go-to-market strategy involves partnering with existing ride-hail platforms like Uber, Lyft and Via to give customers rides. Motional has stated its goal of launching a robotaxi service using driverless Hyundai Ioniq 5 vehicles in 2024.
Motional and Hyundai announced plans in November 2023 to co-develop production-ready versions of the all-electric Ioniq 5 robotaxi at the automaker’s new innovation center in Singapore, the Hyundai Motor Group Innovation Center Singapore (HMGICS). During CES 2024, Motional also announced plans to work with Kia on a next-generation vehicle that will enter commercial operations later this decade, with initial development stages beginning this year.
Motional’s financial shifts come as the robotaxi industry continues to face uncertainty. The startup has been inching slowly towards commercialization, launching pilots in at least five cities. Crucially, Motional has not yet begun charging for rides or deliveries yet. Meanwhile among the competition, Waymo continues to expand its fully driverless, paid robotaxi service in San Francisco, Los Angeles and Phoenix, with plans to hit Austin later this year. GM’s Cruise is still mainly off the streets after an incident in October 2023 that left a pedestrian stuck under and dragged by one of its robotaxis, but the company has begun mapping again in Phoenix as part of a slow, deliberate reintroduction to public roads.
Then there’s Tesla. CEO Elon Musk has shaken up his company, laying off thousands and increasing investment into AI, in a stated goal to go “balls to the walls for autonomy” and deliver a robotaxi in August.
Wander the pits at any professional motorsports event, especially something like Formula 1, and you’ll see endless computer displays full of telemetry. Modern teams are awash in real-time digital feedback from the cars. I’ve been in many of these pits over the years and marveled at the streams of data, but never have I seen an instance of the Microsoft Visual Studio software development suite running there right amid the chaos.
But then, I’ve never attended anything like the inaugural Abu Dhabi Autonomous Racing League event this past weekend. The A2RL, as it is known, is not the first autonomous racing series: There’s the Roborace series, which saw autonomous race cars setting fast lap times while dodging virtual obstacles; and the Indy Autonomous Challenge, which most recently ran at Las Vegas Motor Speedway during CES 2024.
While the Roborace focused on single-car time trials and the Indy Autonomous series centers on oval action, A2RL set out to break new ground in a couple of areas.
A2RL put four cars on track, competing simultaneously for the first time. And, perhaps more significantly, it pitted the top-performing autonomous car against a human being, former Formula 1 pilot Daniil Kvyat, who drove for various teams between 2014 and 2020.
The real challenge was behind the scenes, with teams staffed with an impressively diverse cadre of engineers, ranging from fledgling coders to doctorate students to full-time race engineers, all fighting to find the limit in a very new way.
Unlike Formula 1, where 10 manufacturers design, develop and produce completely bespoke cars (sometimes with the help of AI), the A2RL race cars are entirely standardized to provide a level playing field. The 550-horsepower machines, borrowed from the Japanese Super Formula Championship, are identical, and the teams are not allowed to change a single component.
That includes the sensor array, which features seven cameras, four radar sensors, three lidar sensors and GPS to boot — all of which are used to perceive the world around them. As I would learn while wandering the pits and chatting to the various teams, not everybody is fully tapping into the 15 terabytes of data each car hoovers up every single lap.
Some teams, like the Indianapolis-based Code 19, only started work on the monumental project of creating a self-driving car a few months ago. “There’s four rookie teams here,” said Code 19 co-founder Oliver Wells. “Everyone else has been competing in competitions just like this, some of them for up to seven years.”
Munich-based TUM and Milan-based Polimove have extensive experience running and winning in both Roborace and the Indy Autonomous Challenge. That experience carries over, as does the source code.
“On the one hand, the code is continuously developed and improved anyway,” said Simon Hoffmann, team principal at TUM. The team made adjustments to change the cornering behavior to suit the sharper turns in the road course and also adjust the overtaking aggression. “But in general, I would say we use the same base software,” he said.
Through the series of numerous qualifying rounds throughout the weekend, the teams with the greatest experience dominated the timing charts. TUM and Polimove were the only two teams to complete lap times in less than two minutes. Code 19’s fastest lap, however, was just over three minutes; the other new teams were far slower.
This has created a competition that’s rarely seen in software development. While there have certainly been previous competitive coding challenges, like TopCoder or Google Kick Start, this is a very different sort of thing. Improvements in code mean faster lap times — and fewer crashes.
Kenna Edwards is a Code 19 assistant race engineer and a student at Indiana University. She brought some previous app development experience to the table, but had to learn C++ to write the team’s antilock braking system. “It saved us at least a couple of times from crashing,” she said.
Unlike traditional coding problems that might require debuggers or other tools to monitor, improved algorithms here have tangible results. “A cool thing has been seeing the flat spots on the tire improve over the next session. Either they’ve reduced in size or in frequency,” Edwards said.
This implementation of theory not only makes for engaging engineering challenges but also opens up viable career paths. After earlier interning with Chip Ganassi Racing and General Motors, and thanks to her experience with Code 19, Edwards starts full-time at GM Motorsports this summer.
That sort of development is a huge part of what A2RL is about. Shadowing the main on-track action is a secondary series of competitions for younger students and youth groups around the world. Before the main A2RL event, those groups competed with autonomous 1:8-scale model cars.
“The aim is, next year, we keep for the schools the smaller model cars, we’ll keep for the universities maybe doing it on go-karts, a bit bigger, they can play with the autonomous go-karts. And then, if you want to be in the big league, you start racing on these cars,” said Faisal Al Bannai, the secretary general of Abu Dhabi’s Advanced Technology Research Council, the ATRC. “I think by them seeing that path, I think you’ll encourage more guys to come into research, to come into science.”
It’s Al Bannai’s ATRC that’s footing the bill for the A2RL, covering everything from the cars to the hotels for the numerous teams, some of whom have been testing in Abu Dhabi for months. They also put on a world-class party for the main event, complete with concerts, drone races, and a ridiculous fireworks show.
The on-track action was a little less spectacular. The first attempt at a four-car autonomous race was aborted after one car spun, blocking the following cars. The second race, however, was far more exciting, featuring a pass for the lead when the University of Modena’s Unimore team car went wide. It was TUM that made the pass and won the race, taking home the lion’s share of the $2.25 million prize purse.
As for man vs. machine, Daniil Kvyat made quick work of the autonomous car, passing it not once but twice to huge cheers from the assembled crowd of more than 10,000 spectators who took advantage of free tickets to come see a little bit of history — plus around 600,000 more streaming the event.
The technical glitches were unfortunate. Still it was a remarkable event to witness and illustrated how far autonomy has come — and of course, how much more progress needs to be made. The fastest car was still upwards of 10 seconds off of Kvyat’s time. However, it ran smooth, clean laps at an impressive speed. That’s in stark contrast to the first DARPA Grand Challenge in 2004, which saw every single competitor either crashing into a barrier or meandering off into the desert on an unplanned sojourn.
For A2RL, the real test will be whether it can evolve into a financially viable series. Advertising drives most motorsports, but here, there’s the added benefit of developing algorithms and technologies that manufacturers could reasonably apply in their cars.
ATRC’s Al Bannai told me that while the series organizers own the cars, the teams own the code and are free to license it: “What they compete on at the moment is the algorithm, the AI algorithm that makes this car do what it does. That belongs to each of the teams. It doesn’t belong to us.”
The real race, then, might not be on the track, but in securing partnerships with manufacturers. After all, what better way to inspire confidence in your autonomous technology than by showing it can handle traffic on the race track at 160 mph?
Seven Waymo robotaxis blocked traffic moving onto the Potrero Avenue 101 on-ramp in San Francisco on Tuesday at 9:30 p.m., according to video of the incident posted to Reddit and confirmation from Waymo.
While routing back to Waymo’s city depot that evening, the first robotaxi in the lineup came across a road closure with traffic cones. The only other path available to the vehicles was to take the freeway, according to a Waymo spokesperson. California regulators recently approved Waymo to operate its autonomous robotaxi service on San Francisco freeways without a human driver, but the company is still only testing on freeways with a human driver in the front seat. Waymo told TechCrunch it is first prioritizing a safe and gradual scale of rider-only freeway operations in Arizona before advancing in California.
After hitting the road closure, the first Waymo vehicle in the lineup then pulled over out of the traffic lane that was blocked by cones, followed by six other Waymo robotaxis. Human-driven cars were then stuck behind some of the robotaxis; a video posted online shows fed-up drivers getting out of their cars to physically move the cones out of the way so they could pass both the road closure and the stalled Waymos.
Waymo told TechCrunch it immediately dispatched its Roadside Assistance team to manually retrieve the vehicles, and that the whole event lasted no longer than 30 minutes.
It’s not the first time Waymo vehicles have caused a road blockage, but this is the first documented incident involving a freeway. Cruise, GM’s autonomous vehicle subsidiary, has come under scrutiny for multiple cases of its vehicles malfunctioning and blocking traffic, first responders and public transit. Of course, human drivers block traffic all the time, but city officials and first responders in San Francisco have expressed frustration with both not being able to access and move robotaxis when they’re in the way, and also not being able to issue traffic citations to the vehicles. In San Francisco, there must be a driver in the car in order to issue a citation.
Waymo, the self-driving company under Alphabet, began testing its robotaxis in Atlanta on Tuesday, adding another city to its ever-expanding testing and deployment domain.
Over the next few months, Waymo will deploy a handful of cars driven manually by humans to gather mapping data and get familiar with Atlanta’s environment, Sandy Karp, a Waymo spokesperson, told TechCrunch. Later, Waymo aims to test its robotaxis in Atlanta without the safety driver in the front seat.
Like many other states, Georgia’s regulation of AVs is almost nonexistent, meaning Waymo can technically drop fully autonomous vehicles on the streets today without a safety driver, provided it meets the state’s minimal risk conditions.
Waymo declined to comment on whether it plans to launch commercially in Atlanta, or any of the other cities in which it has started collecting mapping data. Earlier this month, Waymo began mapping Washington, D.C., and in November 2023, the company began winter testing robotaxis in Buffalo.
“We’re laser focused on scaling our fully autonomous Waymo One ride-hailing service in the cities where we operate, as we continue safely and responsibly advancing our autonomous technology through road trips to various cities around the U.S.,” said Karp.
Atlanta is just the latest in a string of territorial gains for Waymo over the last few months. Just last week, Waymo officially launched paid robotaxi rides in Los Angeles. In March, California regulators approved Waymo to grow its commercial robotaxi service across the San Francisco peninsula and on San Francisco freeways, which unlocks a route to San Francisco International Airport. Waymo has been offering rides to and from Phoenix’s airport since November 2022, and recently expanded to include curbside dropoff and pickup.
Waymo also started giving driverless rides to employees in Austin in March and plans to open up the service to members of the public later this year.
Waymo’s recent wins are reminiscent of its erstwhile competitor Cruise’s increased activity last year. By August 2023, Cruise had announced initial data collection in Atlanta, alongside Seattle, Washington D.C., Las Vegas and other cities. Cruise had also begun testing its robotaxis Austin, Houston, Dallas and Miami and operating a limited robotaxi service in Phoenix.
Cruise’s expansion plans came to a sudden halt after an October 2 incident in San Francisco that led to suspended permits and a decision to ground its entire fleet. (The California Department of Motor Vehicles tells us Cruise is in the process of trying to get its permits in the state back.)
It’s important to note that Waymo and Cruise are not the same. Cruise has faced scrutiny for its robotaxis malfunctioning in public roads, blocking the flow of traffic, public transit and first responders. Waymo has been touted as a company that has moved slower and broken fewer things, but the company and its tech are not without their faults.
In February, Waymo recalled the software that powers its robotaxi fleet after two vehicles crashed into the same towed pickup truck in Phoenix in December. A Waymo robotaxi also hit and killed a dog in June 2023.
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