Steering control for vehicles

US10829149B1 · kind B1 · utility

Assignee

• Zoox, Inc. · US

Inventors

• Gowtham Garimella · Hayward, US
• Joseph Funke · Redwood City, US
• Chuang Wang · Sunnyvale, US
• Marin Kobilarov · Baltimore, US

Key dates

• Filing date: Dec 13, 2017
• Grant date: Nov 10, 2020
• Expiry date: Oct 17, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/08
• WIPO field: Control
• WIPO sector: Instruments

Abstract

Model-based control of dynamical systems typically requires accurate domain-specific knowledge and specifications system components. Generally, steering actuator dynamics can be difficult to model due to, for example, an integrated power steering control module, proprietary black box controls, etc. Further, it is difficult to capture the complex interplay of non-linear interactions, such as power steering, tire forces, etc. with sufficient accuracy. To overcome this limitation, a recurring neural network can be employed to model the steering dynamics of an autonomous vehicle. The resulting model can be used to generate feedforward steering commands for embedded control. Such a neural network model can be automatically generated with less domain-specific knowledge, can predict steering dynamics more accurately, and perform comparably to a high-fidelity first principle model when used for controlling the steering system of a self-driving vehicle.