Tesla's camera-only Cybercab is set to enter a robotaxi market where safety has largely been defined by Waymo's reliance on a heavy stack of LiDAR, radar, and ultrasonic sensors. The minimalist approach raises fundamental questions about whether vision alone can handle the edge cases that have historically tripped up autonomous driving systems, from adverse weather to complex urban intersections. Industry experts are split on whether Tesla's confidence in its neural network capabilities represents a genuine technological leap or an overreach that could slow its path to safe, large-scale deployment. The debate sits at the heart of a broader question: is the future of self-driving cars built on redundancy and layered sensing, or can a single modality, paired with enough data, close the gap?
Tesla's camera-only Cybercab enters a robotaxi market dominated by Waymo's multi-sensor approach. Experts question whether Tesla's minimalist technology can safely scale to compete with rivals using ...
