Waymo and Cybercab use very different sensors – which wins determines SDV future (asteriskmag.com)

Waymo and Tesla's Cybercab are showcasing two contrasting approaches to autonomous vehicle (AV) technology as they operate their robotaxi services in Austin, Texas. Waymo employs a comprehensive suite of sensors, including lidar and radar, to build a detailed 3D model of its environment, enhancing the vehicle's ability to detect obstacles and navigate complex situations. In contrast, Tesla's Cybercab relies solely on eight cameras and neural network processing, a philosophy that argues human-like vision and computation can achieve full autonomy without the additional cost and complexity of lidar. The outcome of this competition is significant for the AI/ML community because it may redefine the standards for AV development. If Tesla's vision-only model proves effective, it could lower production costs and expedite the deployment of autonomous taxis. With the global taxi market projected to grow significantly, the choice between sensor fusion and vision-centric strategies will shape the future of urban transportation, impacting everything from operational efficiency to consumer access. This showdown not only tests differing technological philosophies but also highlights broader implications for the commercialization and scalability of AVs in complex urban environments.