NVIDIA Corporation (20240239374). BEHAVIOR PLANNING FOR AUTONOMOUS VEHICLES simplified abstract

BEHAVIOR PLANNING FOR AUTONOMOUS VEHICLES

Organization Name

NVIDIA Corporation

Inventor(s)

David Nister of Bellevue WA (US)

Yizhou Wang of San Jose CA (US)

Julia Ng of San Jose CA (US)

Rotem Aviv of San Diego CA (US)

Seungho Lee of San Jose CA (US)

Joshua John Bialkowski of San Mateo CA (US)

Hon Leung Lee of Bellevue WA (US)

Hermes Lanker of Zürich (CH)

Raul Correal Tezanos of Santa Clara CA (US)

Zhenyi Zhang of San Jose CA (US)

Nikolai Smolyanskiy of Seattle WA (US)

Alexey Kamenev of Carlsbad CA (US)

Ollin Boer Bohan of Redmond WA (US)

Anton Vorontsov of San Jose CA (US)

Miguel Sainz Serra of Palo Alto CA (US)

Birgit Henke of Seattle WA (US)

BEHAVIOR PLANNING FOR AUTONOMOUS VEHICLES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240239374 titled 'BEHAVIOR PLANNING FOR AUTONOMOUS VEHICLES

The abstract of this patent application describes a technology that selects a preferred trajectory for an autonomous vehicle by evaluating multiple hypothetical trajectories based on different components within a planning system. The optimization score provided by each component allows for competing priorities such as comfort, minimal travel time, and fuel economy to be considered together in selecting the best trajectory.

• Evaluates multiple hypothetical trajectories for autonomous vehicles
• Components provide optimization scores based on priorities such as comfort, travel time, and fuel economy
• Final optimization score is determined by combining scores from multiple components
• Allows for competing priorities to be considered together in selecting the best trajectory
• Iterative approach used to identify optimal trajectory for autonomous vehicles

Potential Applications: - Autonomous driving systems - Transportation and logistics industry - Smart city infrastructure

Problems Solved: - Selecting the best trajectory for autonomous vehicles based on multiple competing priorities - Optimizing comfort, travel time, and fuel economy in trajectory planning

Benefits: - Improved efficiency and safety in autonomous vehicle navigation - Enhanced user experience through optimized trajectory selection - Reduction in fuel consumption and environmental impact

Commercial Applications: Title: Autonomous Vehicle Behavior Planning System This technology can be applied in autonomous vehicle systems for transportation companies, smart city initiatives, and logistics companies to enhance route planning and optimize vehicle performance.

Questions about Autonomous Vehicle Behavior Planning System: 1. How does the technology evaluate multiple hypothetical trajectories for autonomous vehicles? 2. What are the key benefits of using this behavior planning system in autonomous vehicles?

Frequently Updated Research: Research on the optimization of trajectory planning algorithms for autonomous vehicles is ongoing, with a focus on improving efficiency and safety in navigation systems.

Original Abstract Submitted

embodiments of the present disclosure relate to behavior planning for autonomous vehicles. the technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. the various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. this scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. in examples, the trajectory with the best combined score may be selected for implementation. as such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.