Netradyne, Inc.

Veeresh Taranalli

David Jonathan Julian

Arvind Yedla

Venkata Ramanan Venkatachalam Jayaraman

Venkata Sreekanta Reddy Annapureddy

Michael Campos

Jonathan Albert Cox

Sandeep Pandya

Adam David Kahn

Badugu Naveen Chakravarthy

Jaeyoon Kim

Dale Alan Willis

Avneesh Agrawal

Suresh Babu Yanamala

Systems and methods are provided for intelligent driving monitoring systems, advanced driver assistance systems and autonomous driving systems, and providing alerts to the driver of a vehicle, based on anomalies detected between driver behavior and environment captured by the outward facing camera. Various aspects of the driver, which may include his direction of sight, point of focus, posture, gaze, is determined by image processing of the upper visible body of the driver, by a driver facing camera in the vehicle. Other aspects of environment around the vehicle captured by the multitude of cameras in the vehicle are used to correlate driver behavior and actions with what is happening outside to detect and warn on anomalies, prevent accidents, provide feedback to the driver, and in general provide a safer driver experience.

Inward/outward vehicle monitoring for remote reporting and in-cab warning enhancements

The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Traffic boundary mapping

A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

System and method of determining a curve

Growing community of inventors

San Diego, CA, United States of America

Veeresh Taranalli