The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 04, 2026

Filed:

Apr. 30, 2024
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Kshitij Agarwal, San Mateo, CA (US);

Sven Brüggemann, San Francisco, CA (US);

Amir Takhmar, Mountain View, CA (US);

Pengzhi Tian, Dublin, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60W 60/00 (2020.01); B60W 50/04 (2006.01); G07C 5/08 (2006.01);
U.S. Cl.
CPC ...
B60W 60/0015 (2020.02); B60W 50/04 (2013.01); G07C 5/0841 (2013.01); B60W 2554/802 (2020.02);
Abstract

Data-driven techniques are described herein for determining collision probabilities and/or predicted collision rates associated with vehicle control components used in autonomous vehicles. A performance modeling system may determine a first vehicle-distance-to-object distribution, based on log data captured in real-world driving environments. A second tracking error distribution may be received and/or determined associated with one or more vehicle control components, and the performance modeling system may determine collision probabilities and/or rates associated with the vehicle control components based on the distributions. In various examples, these techniques can be used to determine target error distributions associated with particular vehicle control components and/or particular driving maneuvers, based on overall safety and performance target metrics for an autonomous vehicle. Additionally, these techniques also can be used to predict the overall collision probability metrics for an autonomous vehicle based on tracking error distributions associated with individual vehicle control components.


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