面向自動(dòng)駕駛運(yùn)行風(fēng)險(xiǎn)的高風(fēng)險(xiǎn)關(guān)鍵道路辨識(shí)

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中圖分類號(hào)：F570 文獻(xiàn)標(biāo)志碼：ADOI： 10.13714/j.cnki.1002-3100.2025.09.018

Abstract： Autonomous driving technology has been deployed in some open road areas， exposing a series safety risks. These safety risks accidents frequently occur on high-risk critical roads within operational areas. To enhance safety management risk prevention for autonomous driving， it is essential to identify high-risk critical roads. This paper pro posesa method for identifying high-risk roads based on autonomous driving operational risks. Firstly，a structured risk scenario repository is constructed. networks are segmentedinto topological unitsvia feature-based division. Then， LLMs are employed to generate driving scenarios convert m into topological graphs. Finally， sub graph isomorphism matching is implemented between scenarios repository， with criticality ranking enabling accurate identification high-risk road sections. Compared with state---art methods， proposed approach demonstrates substantial improvements in both recognition accuracy computational efficiency.

Keywords： traffic engineering;high-risk critical roads identification; topological matching; autonomous driving; large language model

0引言

隨著自動(dòng)駕駛技術(shù)的快速發(fā)展，安全問題仍然是制約其規(guī)模化和商業(yè)化的關(guān)鍵瓶頸。（剩余8583字）