Waymo llc (20240278803). AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS simplified abstract

AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS

Organization Name

waymo llc

Inventor(s)

Hang Zhao of Sunnyvale CA (US)

Jiyang Gao of Foster City CA (US)

Chen Sun of Great Neck NY (US)

Yi Shen of Sunnyvale CA (US)

Yuning Chai of San Mateo CA (US)

Cordelia Luise Schmid of Saint Ismier (FR)

Congcong Li of Cupertino CA (US)

Benjamin Sapp of Marina del Rey CA (US)

Dragomir Anguelov of San Francisco CA (US)

Tian Lan of Sunnyvale CA (US)

Yue Shen of Mountain View CA (US)

AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240278803 titled 'AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS

The patent application describes methods, computer systems, and apparatus for predicting future trajectories for an agent in an environment.

• The system obtains scene context data characterizing the environment, including data that characterizes a trajectory of an agent in the vicinity of a vehicle up to a current time point.
• It identifies a plurality of initial target locations in the environment and generates predicted likelihood scores for each target location representing the likelihood that it will be the intended final location for a future trajectory of the agent.
• For a subset of target locations, the system generates predicted future trajectories for the agent starting from the current time point.
• The system selects likely future trajectories of the agent based on the predicted future trajectories.

1. 1. 1. Potential Applications:

- Autonomous driving systems - Robotics navigation - Predictive analytics for traffic management

1. 1. 1. Problems Solved:

- Improving safety in autonomous vehicles - Enhancing efficiency in route planning - Optimizing decision-making for agents in dynamic environments

1. 1. 1. Benefits:

- Increased accuracy in predicting future trajectories - Enhanced navigation capabilities for agents - Improved overall performance in various applications

1. 1. 1. Commercial Applications:

Predictive analytics software for autonomous vehicles and robotics industries

1. 1. 1. Questions about the Technology:

1. How does this technology improve safety in autonomous vehicles? 2. What are the key factors influencing the accuracy of predicted future trajectories?

1. 1. 1. Frequently Updated Research:

Stay updated on the latest advancements in predictive analytics for autonomous systems and robotics to enhance navigation and decision-making processes.

Original Abstract Submitted

methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for predicting future trajectories for an agent in an environment. a system obtains scene context data characterizing the environment. the scene context data includes data that characterizes a trajectory of an agent in a vicinity of a vehicle in an environment up to a current time point. the system identifies a plurality of initial target locations in the environment. the system further generates, for each of a plurality of target locations that each corresponds to one of the initial target locations, a respective predicted likelihood score that represents a likelihood that the target location will be an intended final location for a future trajectory of the agent starting from the current time point. for each target location in a first subset of the target locations, the system generates a predicted future trajectory for the agent that is a prediction of the future trajectory of the agent given that the target location is the intended final location for the future trajectory. the system further selects, as likely future trajectories of the agent starting from the current time point, one or more of the predicted future trajectories.