Automotive Sensing involves the use of various sensors in vehicles to gather data about the vehicle’s surroundings, monitor its internal systems, and enable advanced driver assistance systems (ADAS) or autonomous driving capabilities. Automotive sensing technologies include cameras, radar, lidar, ultrasonic sensors, and other sensors that provide information for navigation, collision avoidance, and overall vehicle safety.

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Mosaic: Leveraging Diverse Reflector Geometries for Omnidirectional Around-Corner Automotive Radar

A large number of traffic collisions occur as a result of obstructed sight lines, such that even an advanced driver assistance system would be unable to prevent the crash. Recent work has proposed the use of around-the-corner radar systems to detect vehicles, pedestrians, and other road users in these occluded regions. Through comprehensive measurement, we show that these existing techniques cannot sense occluded moving objects in many important real-world scenarios. To solve this problem of limited coverage, we leverage multiple, curved reflectors to provide comprehensive coverage over the most important locations near an intersection. In scenarios where curved reflectors are insufficient, we evaluate the relative benefits of using additional flat planar surfaces. Using these techniques, we more than double the probability of detecting a vehicle near the intersection in three real urban locations and enable NLoS radar sensing using an entirely new class of reflectors.