US 12,272,138 B1
Forward collision warning
Rohit Annigeri, Santa Clara, CA (US); Sharan Srinivasan, Sunnyvale, CA (US); Kevin Lai, Redmond, WA (US); Jose Cazarin, Calgary (CA); Brian Westphal, Livermore, CA (US); Shiva Bala, San Diego, CA (US); Ivan Stoev, Santa Barbara, CA (US); Douglas Boyle, Verdi, NV (US); Cole Jurden, Kansas City, MO (US); Margaret Irene Finch, Austin, TX (US); Rachel Demerly, New York, NY (US); Maya Krupa, Souh Lake Tahoe, CA (US); Shirish Nair, Shoreline, WA (US); Nathan Hurst, Seattle, WA (US); Yan Wang, Mercer Island, WA (US); Shaurye Aggarwal, Evanston, IL (US); and Akshay Raj Dhamija, Campbell, CA (US)
Assigned to Samsara Inc., San Francisco, CA (US)
Filed by Samsara Inc., San Francisco, CA (US)
Filed on Jun. 21, 2024, as Appl. No. 18/750,793.
Int. Cl. G06V 20/40 (2022.01); B60Q 9/00 (2006.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/94 (2022.01); G06V 20/58 (2022.01)
CPC G06V 20/44 (2022.01) [B60Q 9/008 (2013.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/945 (2022.01); G06V 10/95 (2022.01); G06V 20/46 (2022.01); G06V 20/58 (2022.01)] 20 Claims
OG exemplary drawing
 
11. A system comprising:
a memory comprising instructions; and
one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the system to perform operations comprising:
training a first collision warning (CW) classifier with training data comprising images of a road ahead taken from vehicles, speed of the vehicles, and labels indicating occurrence of a collision; and
periodically estimating a probability of a collision at a first vehicle, wherein estimating the probability of the collision comprises:
processing, by a frame feature extractor, a new image frame of an image of the road ahead of the first vehicle to obtain a new feature vector of the new image frame;
accessing a previous state comprising a plurality of previous feature vectors:
creating a current state by discarding, from the previous state, the previous feature vector of an oldest image frame and adding the new image frame to generate a plurality of current feature vectors;
providing as input the current state with the plurality of current feature vectors to the first CW classifier that outputs the probability of collision; and
generating an alert in the first vehicle based on the probability of collision.