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:
Jun. 16, 2026

Filed:

Aug. 14, 2025
Applicant:

Chang'an University, Xi'an, CN;

Inventors:

Ruru Hao, Xi'an, CN;

Zhou Zhou, Xi'an, CN;

Difei Zhang, Xi'an, CN;

Licheng Zhang, Xi'an, CN;

Rongtao Qiu, Xi'an, CN;

Xin Cheng, Xi'an, CN;

Yi Li, Xi'an, CN;

Zhishun Wang, Xi'an, CN;

Xuming Shang, Xi'an, CN;

Jiahui Wang, Xi'an, CN;

Assignee:

CHANG'AN UNIVERSITY, Xi'an, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 50/04 (2006.01); B60W 30/12 (2020.01); B60W 30/18 (2012.01); B60W 50/00 (2006.01); B60W 60/00 (2020.01); G06F 30/15 (2020.01);
U.S. Cl.
CPC ...
B60W 50/045 (2013.01); B60W 50/0098 (2013.01); B60W 60/001 (2020.02); G06F 30/15 (2020.01); B60W 30/12 (2013.01); B60W 30/18163 (2013.01); B60W 2050/0031 (2013.01); B60W 2552/10 (2020.02); B60W 2554/4041 (2020.02); B60W 2554/802 (2020.02); B60W 2554/804 (2020.02); B60W 2720/106 (2013.01);
Abstract

A method, system, apparatus, and medium for generating critical scenarios in autonomous driving tests are provided. The method includes: generating an initial scenario based on a lane-coordinate system; constructing a one-way single-lane car-following scenario, specifically including: creating a road and vehicles based on the initial scenario, the vehicles including an autonomous vehicle controlled by an intelligent driving model (IDM) and an agent vehicle; constructing a one-way dual-lane cut-in scenario, specifically including: creating a dual-lane road and vehicles based on the initial scenario, the vehicles including an autonomous vehicle controlled by the IDM model and an intelligent-agent vehicle; and generating, based on the constructed one-way single-lane car-following scenario and the constructed one-way dual-lane cut-in scenario, critical scenarios for autonomous-vehicle testing. The method efficiently and accurately produces critical scenarios for autonomous-driving systems, thereby accelerating the testing and verification of their performance and safety in complex, high-risk environments.


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