Waymo's autonomous vehicles rely on a sophisticated sensor suite, combining cameras, lidar, and radar for comprehensive environmental perception. These three sensing modalities offer complementary physical properties and provide a full 360-degree view around the vehicle.
Dmitri Dolgov, co-CEO of Waymo, explains that this integrated sensor data is processed by artificial intelligence to make real-time driving decisions. AI acts as the backbone of the Waymo driver, enabling it to determine optimal driving actions based on the vast amount of processed sensor input.
Achieving full autonomy presents significant challenges, extending beyond simple input-output models. Dolgov highlights the complexity of driving as a multi-agent social interaction, akin to modeling dialogue, where the actions of one vehicle affect others. This iterative learning and evolution process, rather than singular breakthroughs, drives advancements in AI for self-driving technology.
Evaluative models within these systems are crucial for assessing driving behavior, identifying both good and bad actions to continuously refine algorithms and improve overall safety and performance.