Rivian CEO RJ Scaringe has made it clear that the company’s approach to autonomous driving sharply differs from Tesla’s, emphasizing that LiDAR remains a critical and safer technology in building reliable self-driving systems.
Speaking on The Verge’s Decoder podcast, Scaringe said Rivian sees “real benefit” in using LiDAR as part of a multi-sensor setup that helps vehicles perceive their surroundings more accurately.
“Our view is that it’s definitely beneficial, and our approach to sensors has been that we need to rapidly build our foundation model as fast as possible,” he said.
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He explained that Rivian’s autonomous driving vision relies on feeding as much sensory data as possible into its AI models.
“Now, what’s happened is that we no longer run the models like that. The models benefit from the maximum amount of information on the front of the model,” Scaringe said, noting that early models in the industry struggled to process inputs from multiple sensors.
Scaringe added that LiDAR’s dramatic drop in cost has made it more viable for commercial use. “The cost of LiDAR used to be tens of thousands of dollars. It’s now low — a couple of hundred bucks,” he said. “It’s a really great sensor that can do things that cameras can’t.”
Rivian’s stance stands in sharp contrast to Elon Musk’s long-held rejection of LiDAR technology, which the Tesla chief executive has called both redundant and inefficient. Musk has often mocked the use of LiDAR and radar, insisting that Tesla’s “vision-only” approach — which uses cameras and neural networks — is sufficient to achieve full autonomy.
In August, Musk reiterated this stance in a post on X, arguing that combining LiDAR and radar with cameras results in “sensor contention” and “increased, not decreased, risk.” He went as far as to claim that this complexity explains why Alphabet’s Waymo — which uses LiDAR, radar, and cameras — cannot handle open-highway driving.
At Tesla’s “Autonomy Day” in 2019, Musk was even more dismissive. “In cars, it’s friggin stupid. It’s expensive and unnecessary. Once you solve vision, it’s worthless,” he said.
However, growing incidents from real-world driving appear to favor Scaringe’s position. LiDAR-equipped systems used by automakers such as Rivian, Waymo, and Ford have recorded significantly fewer safety incidents compared to Tesla’s Full Self-Driving (FSD) vehicles, which depend solely on cameras.
According to recent safety data published by the U.S. National Highway Traffic Safety Administration (NHTSA), Tesla’s camera-powered FSD and Autopilot systems have been involved in multiple reported crashes, some fatal, often linked to system misidentification of obstacles, poor performance in low-light conditions, and driver overreliance. By contrast, companies using LiDAR and radar-assisted systems — including Rivian’s advanced driver-assistance suite — have not been associated with widespread safety investigations or fatal crashes.
Safety experts say the key advantage of LiDAR is its ability to measure depth and distance with high precision, even in poor lighting or weather conditions where camera systems can fail. LiDAR (Light Detection and Ranging) works by bouncing laser pulses off surrounding objects to create a detailed 3D map of the environment, allowing vehicles to “see” their surroundings independent of visible light.
Ford CEO Jim Farley has also described LiDAR as “mission critical” to achieving safe autonomous driving. At the Aspen Ideas Festival in June, he said LiDAR outperforms cameras in difficult driving scenarios, such as bright sunlight or fog.
“While the camera will be completely blinded by the sun, the LiDAR system will still be able to monitor its surroundings,” Farley said, noting that Ford’s driver-assistance technologies rely on multi-sensor redundancy for safety.
The growing divergence between automakers over the role of LiDAR points to a deeper philosophical divide in the race toward full autonomy. Tesla continues to push forward with its camera-only Full Self-Driving model, betting on neural network training to overcome sensory limitations. In contrast, Rivian, Ford, and Alphabet’s Waymo are leaning into multi-sensor designs that combine LiDAR, radar, and cameras — an approach researchers say offers more reliable and safer performance under varied driving conditions.
Scaringe’s remarks reaffirm Rivian’s commitment to building a safety-first autonomous platform powered by multiple perception technologies. The decision has been applauded by many as the company is steadily ramping up production of its R1T pickup, R1S SUV, and electric delivery vans.