Designing Crash-Proof Autonomous Vehicles


Autonomous vehicles keep crashing into things, even though ADAS technology promises to make driving safer because machines can think and react faster than human drivers. Humans rely on seeing and hearing to assess driving conditions. When drivers detect objects in front of the vehicle, the automatic reaction is to slam on the brakes or swerve to avoid them. Quite often drivers cannot react q... » read more

Streamlining Vehicular Electrical System Design And Verification


Automobiles and other road vehicles such as trucks and buses have always been one of the most demanding applications for mechanical and electrical design. Systems must operate properly over a wide range of environmental conditions, facing extremes of temperature, humidity, sunlight, dirt, vibration and more. User expectations of reliability and availability mandate safety-critical design practi... » read more

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving


Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to perform detection and prediction tasks. We extend the BEV network ... » read more