US 11,945,440 B2
Data driven rule books
Andrea Censi, Somerville, MA (US); Kostyantyn Slutskyy, Singapore (SG); Asvathaman Asha Devi, Singapore (SG); Chua Zhe Xuan, Singapore (SG); and Zhiliang Chen, Singapore (SG)
Assigned to Motional AD LLC, Boston, MA (US)
Filed by Motional AD LLC, Boston, MA (US)
Filed on Aug. 18, 2020, as Appl. No. 16/996,785.
Claims priority of provisional application 62/891,002, filed on Aug. 23, 2019.
Prior Publication US 2021/0053569 A1, Feb. 25, 2021
Int. Cl. B60W 30/18 (2012.01); G05D 1/00 (2006.01); G08G 1/01 (2006.01)
CPC B60W 30/18159 (2020.02) [B60W 30/18163 (2013.01); G05D 1/0088 (2013.01); G05D 1/0214 (2013.01); G08G 1/0133 (2013.01); G08G 1/0145 (2013.01); B60W 2400/00 (2013.01); B60W 2520/10 (2013.01); B60W 2554/802 (2020.02)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
determining, by at least one processor, driving behavior of a plurality of manually-operated vehicles, each manually-operated vehicle having engaged in traffic merging behavior at a corresponding uncontrolled traffic intersection;
determining, by the at least one processor, an autonomous vehicle driving model comprising a neural network, wherein data associated with manually-operated vehicles is input to the neural network in order to train the neural network to implement an autonomous vehicle driving behavior of an autonomous vehicle driving to merge with traffic at an uncontrolled traffic intersection; and
controlling, by the at least one processor, at least one control function of the autonomous vehicle according to the autonomous vehicle driving model.