US 11,853,072 B2
System and method for real world autonomous vehicle trajectory simulation
Xing Sun, San Diego, CA (US); Wutu Lin, San Diego, CA (US); Liu Liu, San Diego, CA (US); Kai-Chieh Ma, San Diego, CA (US); Zijie Xuan, San Diego, CA (US); and Yufei Zhao, San Diego, CA (US)
Assigned to TUSIMPLE, INC., San Diego, CA (US)
Filed by TuSimple, Inc., San Diego, CA (US)
Filed on Sep. 1, 2022, as Appl. No. 17/901,736.
Application 17/901,736 is a continuation of application No. 16/929,954, filed on Jul. 15, 2020, granted, now 11,435,748.
Application 16/929,954 is a continuation of application No. 15/796,765, filed on Oct. 28, 2017, granted, now 10,739,775, issued on Aug. 11, 2020.
Prior Publication US 2023/0004165 A1, Jan. 5, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G05D 1/02 (2020.01); G05D 1/00 (2006.01); G05B 13/04 (2006.01); G06N 20/00 (2019.01)
CPC G05D 1/0221 (2013.01) [G05B 13/048 (2013.01); G05D 1/0088 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a data processor;
a data collection system interface for receiving perception or sensor data collected from a data collection system, the perception or sensor data including data from at least one image generating device;
a memory for storage of a plurality of trained trajectory prediction models, the plurality of trained trajectory prediction models having been trained using real world training data and simulated driver behaviors;
a trajectory generation module, executable by the data processor, the trajectory generation module being configured to:
generate, by the data processor, a trajectory for an autonomous vehicle, the trajectory corresponding to the perception or sensor data and autonomous vehicle intention data;
execute, by the data processor, at least one of the plurality of trained trajectory prediction models to generate a distribution of predicted vehicle trajectories for each of a plurality of vehicles proximate to the autonomous vehicle based on the perception or sensor data and the autonomous vehicle intention data;
select, by the data processor, at least one predicted vehicle trajectory from the distribution for each proximate vehicle based on pre-defined criteria; and
modify, by the data processor, the trajectory for the autonomous vehicle to avoid the at least one predicted vehicle trajectory for each proximate vehicle; and
an autonomous vehicle control system for the autonomous vehicle configured to cause the autonomous vehicle to traverse the modified trajectory for the autonomous vehicle.