Real time decision making for autonomous driving vehicles

US11137762B2 · kind B2 · utility

Assignee

• BAIDU USA LLC · US

Inventors

• Liangliang Zhang · Beijing, CN
• Hongyi Sun · Sunnyvale, US
• Dong Li · Tangxia, CN
• Jiangtao Hu · Sunnyvale, US
• Jinghao Miao · Sunnyvale, US
• Jiaming Tao · Sunnyvale, US
• Yifei Jiang · Sunnyvale, US

Key dates

• Filing date: Nov 30, 2018
• Grant date: Oct 5, 2021
• Expiry date: Dec 25, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/088
• WIPO field: Control
• WIPO sector: Instruments

Abstract

In one embodiment, a method, apparatus, and system may predict behavior of environmental objects using machine learning at an autonomous driving vehicle (ADV). One or more yield/overtake decisions are made with respect to one or more objects in the ADV's surrounding environment using a data processing architecture comprising at least a first, a second, and a third neural networks, the first, the second, and the third neural networks having been trained with a training data set. Driving signals are generated based at least in part on the yield/overtake decisions to control operations of the ADV.