Complex IP Challenges in Autonomous Vehicles
AVs rely on artificial intelligence (AI) to recognize and interact with their environments. They map their environments primarily using radar, sonar, and lidar technologies that allow the vehicles to “see” their environment. Radar and sonar emit radio and sound waves, respectively, in pulses that reflect off nearby objects and provide the sensors data on a nearby object’s location, distance, speed, and direction of movement.
The AI systems that power AVs must be trained in advance using machine learning to correctly identify objects and stimuli that the AV may encounter. This training must also occur across various environments and conditions the AV may encounter. This training typically produces satisfactory performance under normal circumstances (e.g., driving on standard roadways in dry, sunny conditions), but problems may arise when AVs encounter situations where the environments have been altered, unknown stimuli are present in the environment, or environmental detection technologies are challenged.