US 12,251,631 B2
Game theoretic decision making
Siyu Dai, Cambridge, MA (US); Sangjae Bae, San Jose, CA (US); and David F. Isele, San Jose, CA (US)
Assigned to Honda Motor Co., Ltd., Tokyo (JP)
Filed by Honda Motor Co., Ltd., Tokyo (JP)
Filed on Mar. 29, 2022, as Appl. No. 17/707,043.
Claims priority of provisional application 63/288,101, filed on Dec. 10, 2021.
Prior Publication US 2023/0182014 A1, Jun. 15, 2023
Int. Cl. B60W 60/00 (2020.01); A63F 13/47 (2014.01); A63F 13/803 (2014.01); G06N 7/01 (2023.01)
CPC A63F 13/47 (2014.09) [A63F 13/803 (2014.09); B60W 60/0027 (2020.02); G06N 7/01 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A system for game theoretic decision making, comprising:
a sensor detecting one or more other vehicles and corresponding attributes as an observation;
a memory storing one or more instructions;
a processor executing one or more of the instructions stored on the memory to perform:
constructing a search tree based on the observation, an initial belief, and a vehicle identified as a current opponent vehicle;
performing a Monte Carlo Tree Search (MCTS) on the search tree based on a planning horizon and a time allowance to determine a desired action from a set of ego-actions;
executing, via one or more vehicle systems, the desired action, wherein the desired action include one or more of a lane change, an acceleration action, a deceleration action, or a stopping action;
detecting, via the sensor, an updated observation associated with one or more of the other vehicles;
identifying one or more of the other vehicles to be updated as the current opponent vehicle; and
updating a root node of the search tree based on the current opponent vehicle.