Netradyne, Inc.

Qualcomm Incorporated

Michael Campos

David Jonathan Julian

Venkata Sreekanta Reddy Annapureddy

Adam David Kahn

Sandeep Pandya

Avneesh Agrawal

Arvind Yedla

Tejeswara Rao Gudena

Vinay Kumar Rai

Lance Steven Hetherington

Vikram Makam Gupta

Jonathan Albert Cox

Veeresh Taranalli

Badugu Naveen Chakravarthy

Yinyin Liu

Arun Valiaparambil

Hisham Rahman

Sneha Aenugu

Priyam Bakliwal

Alexander Thomas

Venkata Ramanan Venkatachalam Jayaraman

Victor Hokkiu Chan

Praveen Kumar

Pratik Verma

Suresh Babu Yanamala

Ankur Nigam

Stephan Franklin Dunn

Manoj Venkata Tutika

Venkat Ramanan Venkatachalam Jayaraman

Matthew Karl Drake

Karan Kishore

Hemanth Roy Badugu

Aravind P (Padmasanan)

Anubhav

Jeffrey Alexander Levin

Casimir Matthew Wierzynski

Bardia Fallah Behabadi

Sarah Paige Gibson

Erik Christopher Malone

Naveen Gandham Rao

Vikram Gupta

Edward Liao

Anubhav Gupta

Lakshmi Krishnan

Dihui Lai

Systems and methods are provided for detecting a driving action that mitigates risk.

Detection of driving actions that mitigate risk

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. Combinations of co-occurring driving events may be detected and used to warn on anomalies, prevent accidents, provide feedback to the driver, and in general provide a safer driver experience.

Combination alerts

Systems and methods for curating video and other driving-related data for use in driver coaching, which may include selecting or ranking driving behaviors for coaching, selecting or ranking drivers for coaching, selecting or ranking video and other data to be used in coaching, preparing for, scheduling, and summarizing coaching sessions, matching the format of coaching to the behavior or person being coached, preventing unsafe driving situations, influencing job dispatch decisions based on safety scores, and/or reducing data bandwidth usage based on a determined coaching effectiveness of video data.

Virtual safety manager

Systems, devices and methods provide, implement, and use vision-based methods of sequence inference for a device affixed to a vehicle.

Multiple exposure event determination

Systems and methods are provided for recording video of a driver in a vehicle and a surrounding visual field of the driver. The system includes a detachable body coupled to a windshield of a vehicle. The system further includes three or more cameras coupled to the detachable body. The three or more cameras are configured to capture surrounding views from the detachable body. One of the three or more cameras faces a driver seat of the vehicle in response to the detachable body being coupled to the windshield of the vehicle. The video may be processed by the system, the cloud, or a combination of them.

Recording video of an operator and a surrounding visual field

Systems and methods are provided for determining cause of atypical traffic events and/or encouraging good driving behavior. The systems and methods may involve a camera sensor and/or inertial sensors to detect traffic events, as well analytical methods that may attribute a cause to the traffic event. The systems and methods include a processor that is configured to determine an occurrence of an atypical traffic event at or near a monitored vehicle; and determine a cause of the atypical traffic event based on data collected at the monitored vehicle, wherein the cause of the atypical traffic event is at least one of: a driver or control system of the monitored vehicle; a second driver or second control system of a second vehicle; and a road condition.

Determining causation of traffic events and encouraging good driving behavior

Systems and methods are provided for distributed video storage and search with edge computing. The method may comprise caching a first portion of data on a first device. The method may further comprise determining, at a second device, whether the first device has the first portion of data. The determining may be based on whether the first piece of data satisfies a specified criterion. The method may further comprise sending the data, or a portion of the data, and/or a representation of the data from the first device to a third device.

Distributed video storage and search with edge computing

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

La Jolla, CA, United States of America

Michael Campos