US 12,330,646 B2
Off road assistance
Boaz Mell, Petach Tikva (IL); and Igal Raichelgauz, Tel Aviv (IL)
Assigned to AUTOBRAINS TECHNOLOGIES LTD, Tel Aviv (IL)
Filed by AUTOBRAINS TECHNOLOGIES LTD, Tel Aviv (IL)
Filed on Aug. 3, 2021, as Appl. No. 17/444,375.
Application 17/444,375 is a continuation in part of application No. 17/309,064, previously published as PCT/IB2019/058207, filed on Sep. 27, 2019.
Claims priority of provisional application 62/706,156, filed on Aug. 3, 2020.
Claims priority of provisional application 62/827,122, filed on Mar. 31, 2019.
Claims priority of provisional application 62/750,822, filed on Oct. 26, 2018.
Claims priority of provisional application 62/747,147, filed on Oct. 18, 2018.
Prior Publication US 2022/0032914 A1, Feb. 3, 2022
Prior Publication US 2024/0101115 A9, Mar. 28, 2024
Int. Cl. B60W 60/00 (2020.01); B60W 30/18 (2012.01); B60W 30/182 (2020.01); B60W 40/064 (2012.01); B60W 40/072 (2012.01); B60W 40/076 (2012.01); B60W 50/14 (2020.01); G05B 13/02 (2006.01)
CPC B60W 30/18009 (2013.01) [B60W 30/182 (2013.01); B60W 40/064 (2013.01); B60W 40/072 (2013.01); B60W 40/076 (2013.01); B60W 50/14 (2013.01); B60W 60/001 (2020.02); G05B 13/0265 (2013.01); B60W 2540/215 (2020.02); B60W 2552/05 (2020.02); B60W 2552/15 (2020.02); B60W 2552/30 (2020.02); B60W 2552/35 (2020.02); B60W 2555/20 (2020.02)] 19 Claims
OG exemplary drawing
 
1. A method for off road driving, the method comprises:
obtaining sensed information pertaining to an environment of an ego vehicle, by one of more vehicle sensors of the vehicle and while driving over an off road path;
detecting, by a machine learning process, an occurrence of an off road driving event; wherein the detecting comprises generating a signature of the sensed information by:
performing a first number of signature generating iterations using a convolutional neural network of fixed connectivity; and
performing additional signature generation iterations that involve deactivating, per each additional signature generation iteration, spanning elements that are irrelevant to the additional signature generation iteration;
determining, by the machine learning process, a characteristic behavior of a vehicle of a model similar to the ego vehicle when facing the off road driving event; and
responding, at least in part by the machine learning process, to the occurrence of the off road driving event; wherein the responding is associated with least one of autonomously driving the ego vehicle or autonomously changing a configuration of the ego vehicle;
wherein the machine learning process is trained by a training process that involves:
obtaining off-road information sensed by vehicles of a model similar to model of the ego vehicle; wherein the off-road information comprises environmental off-road information pertaining to the environment of the vehicles and telematic off-road information indicative of characteristic behaviors of the vehicles;
clustering the off-road environmental information to provide a first group of clusters; and
generating a second group of clusters, based on the first group, by clustering the first group of clusters based on the off-road telematic information, such that different clusters of the second group of clusters are associated with different characteristic behaviors of the vehicles of the model similar to the model of the ego vehicle, and each different characteristic behavior is among a defined number of most frequently occurring behaviors of a different off-road event when facing different off road driving events.