Fca US LLC

Ivan Roman

Dalong Li

Loren Michael Trotter

Zijian Wang

Jason Trombley

Andrew Chen

Zachary C Rogalski

An advanced driver assistance system (ADAS) and method for a vehicle utilize a light detection and ranging (LIDAR) system configured to emit laser light pulses and capture reflected laser light pulses collectively forming three-dimensional (3D) LIDAR point cloud data and a controller configured to receive the 3D LIDAR point cloud data, convert the 3D LIDAR point cloud data to a two-dimensional (2D) birdview projection, detect a set of lines in the 2D birdview projection, filter the detected set of lines to remove lines having features that are not indicative of traffic signs to obtain a filtered set of lines, and detect one or more traffic signs using the filtered set of lines.

Traffic sign detection from filtered birdview projection of LIDAR point clouds

An advanced driver assistance system (ADAS) and corresponding method for a vehicle utilize a camera system configured to capture an image and a controller configured to receive the captured image, detect an object in the captured image using a simple neural network model, track the detected object using a tracking technique to obtain a tracked position, project a trajectory of the detected object using a trajectory projection technique to obtain a predicted position, determine a most likely position of the detected object based on at least one of the tracked and predicted positions, generate a two-dimensional (2D) birdview projection illustrating the detected object according to its determined most likely position, and control at least one ADAS feature of the vehicle using the generated 2D birdview projection.

Techniques for using a simple neural network model and standard camera for image detection in autonomous driving

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White Lake, MI, United States of America

Ivan Roman