Samsara Inc.

Shaurye Aggarwal

Yan Wang

Nathan Hurst

Sharan Srinivasan

Margaret Irene Finch

Kevin Lai

Shirish Nair

Cole Jurden

Brian Westphal

Akshay Raj Dhamija

Rohit Annigeri

Rachel Demerly

Jose Cazarin

Douglas Boyle

Maya Krupa

Shiva Bala

Ivan Stoev

Techniques are presented for the detection and management of collision warning (CW) events. A training dataset comprising videos of vehicle collisions and non-collisions, sensor readings, environmental conditions, and more is utilized to train a CW classification model for detecting potential collision events in vehicles. A backend CW classification model, with greater computational resources, employs a more complex neural network to review CW events received by the Behavioral Monitoring System (BMS) based on video data, achieving higher precision and reducing false positives. The CW model is installed in vehicles for real-time detection, while the backend model is deployed at the BMS. The BMS validates detected CW events, filters out false positives, and streamlines the review process for fleet administrators and customers. Additional BMS filtering operations include assessing non-proximity-related CW events and camera impairments, with the filtered CW events presented for review in the safety inbox.

Forward collision warning

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Evanston, IL, United States of America

Shaurye Aggarwal