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Modern driver assistance systems rely on a wide range of sensors (RADAR,LIDAR, ultrasound and cameras) for scene understanding and prediction. Thesesensors are typically used for detecting traffic participants and sceneelements required for navigation. In this paper we argue that relying on camerabased systems, specifically Around View Monitoring (AVM) system has greatpotential to achieve these goals in both parking and driving modes withdecreased costs. The contributions of this paper are as follows: we present anew end-to-end solution for delimiting the safe drivable area for each frame bymeans of identifying the closest obstacle in each direction from the drivingvehicle, we use this approach to calculate the distance to the nearestobstacles and we incorporate it into a unified end-to-end architecture capableof joint object detection, curb detection and safe drivable area detection.Furthermore, we describe the family of networks for both a high accuracysolution and a low complexity solution. We also introduce further augmentationof the base architecture with 3D object detection.

Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System