US 12,391,274 B2
Learning constraints over beliefs in autonomous vehicle operations
Marcell Vazquez-Chanlatte, Palo Alto, CA (US); and Stefan Witwicki, San Carlos, CA (US)
Assigned to Nissan North America, Inc., Franklin, TN (US)
Filed by Nissan North America, Inc., Franklin, TN (US)
Filed on Feb. 28, 2023, as Appl. No. 18/175,747.
Prior Publication US 2024/0286634 A1, Aug. 29, 2024
Int. Cl. B60W 60/00 (2020.01); B60W 50/00 (2006.01); G05B 13/02 (2006.01)
CPC B60W 60/001 (2020.02) [B60W 50/00 (2013.01); G05B 13/0265 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for use in a vehicle, the method comprising:
obtaining sensor data;
obtaining user demonstration data, wherein the user demonstration data is data associated with a sequence of actions and probability distributions of a current state of the vehicle;
determining a belief path based on the sensor data and the user demonstration data using a partially observable Markov decision process (POMDP) model;
determining learned constraints by sampling a constraint and determining counter-factual belief path labels;
updating the belief path based on the learned constraints;
determining candidate actions based on the POMDP model, wherein the candidate actions are constrained by the updated belief path;
selecting an action of the candidate actions that is above a probability threshold; and
controlling the vehicle using the selected action to traverse a vehicle network.