The crashes involving Tesla vehicles striking stationary objects—the crash attenuator in California, a stopped fire truck in Utah in May, and another fire truck in California in January—show the limitations of relying on just cameras and radar, says Raj Rajkumar, director of the Connected and Autonomous Driving Collaborative Research Lab at Carnegie Mellon University in Pittsburgh. Camera-based systems have to be trained to recognize specific images, and if they encounter something in the real world that doesn’t match their expectations, the radar has to pick it up, Rajkumar said.
Tesla’s system missed the fire trucks, and there was also an incident reported in China where a Tesla crashed into a stopped garbage truck. The company’s technology appears to work well with moving objects, but not stationary ones, Rajkumar said.
“Consumers need to be extremely cautious about the claims being made,” Rajkumar said. “There’s a lot of hype.”