Motional Ad LLC

Caglayan Dicle

Eric Wolff

Hamed Kiani Galoogahi

Sammy Omari

Nanxiang Li

Sang Uk Lee

Dmitry S Yershov

A scene simulation system can use scene data of a scene of a vehicle to generate one or more simulated states and one or more simulated trajectories associated with the one or more simulated states. The system can evaluate the simulated trajectories and select an action for the vehicle based on the evaluation of the simulated trajectories.

Vehicle action selection based on simulated states

This disclosure relates in general to systems and methods for optically tracking objects proximate an autonomous vehicle. In particular, an object tracking system capable of refining position data for objects being tracked by determining a location of the objects surrounding the autonomous vehicle at least on part on previously determined locations of the objects. In certain instances, the predicted and detected locations used to arrive at a refined location for the objects can be weighted in different ways depending on conditions of the sensor data and quality of the historical data.

Object tracking supporting autonomous vehicle navigation

This disclosure relates in general to systems and methods for tracking objects proximate an autonomous vehicle. In particular, an object tracking system capable of re-identifying objects it has temporarily lost line of sight to is described. Re-identification of the objects allows earlier object detections to be used more effectively to predict motion likely to be taken by the objects.

Long-term object tracking supporting autonomous vehicle navigation

Provided are methods for generating future maneuver parameters in a planner, which include receiving at least one first set of parameters associated with one or more previous maneuvers of a vehicle and at least one second set of parameters associated with a maneuver goal of the vehicle, generating, using the first and second sets of parameters, a future maneuver parameter corresponding to a future maneuver of the vehicle, training at least one data model by comparing the generated future maneuver parameter to one or more reference maneuver parameters, generating, based on training, a corrected future maneuver parameter. The corrected future maneuver parameter includes a future maneuver of the vehicle and a correction to the future maneuver of the vehicle. The first set of parameters includes the generated corrected future maneuver parameter, which is used to correct at least one first parameter. The training is executed using the corrected first parameter.

Growing community of inventors

Melrose, MA, United States of America

Caglayan Dicle