基于樹結(jié)構(gòu)Parzen估計(jì)器的自動(dòng)駕駛仿真測試關(guān)鍵場景生成方法

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主題詞：自動(dòng)駕駛場景生成TPEMOTPECARLA中圖分類號(hào)：U467.3；TP391.9 文獻(xiàn)標(biāo)志碼：A DOI： 10.19620/j.cnki.1000-3703.20240092

Automatic Generation Method of Autonomous Driving Simulation Test ScenariosBasedon Tree-StructuredParzen Estimator

QinQin'，Yang Zhisheng1，LiDaoxin1，Shen Zhiwei2，Cao Xiaolin3 （1.Shanghai Polytechnic University，Schoolof Intellgent Manufacturingand ControlEngineering，Shanghai 201209; 2.School of Electrical Engineering and Telecommunications，Universityof New South Wales，Sydney 2052; 3.College of Automotive Engineering，Jilin University，Changchun 130015）

【Abstract】In viewof theexponential increase in thenumberof keyscene scenariosgenerated in high-dimensional space，andthediicultyoftraditionalartificialconstructionorrandomsearchmethods tobalancecoverageandeficiencythis paper proposes a search method basedon single-objective Tree structure Parzen Estimator（TPE）and Multi-Objective Tree structureParzen Estimator （MOTPE）.Asoftware-in-the-loopautomatedsimulationtesting framework isbuiltbyusing the CARLA simulator.Taking weather elementsasanexample，thecriticalscenario generationefectsofthediffrent search algorithmsarecompared.Theexperimentalresultsindicate thattheTPE-basedsearch methodandthe MOTPE-based method increase thenumberofkeyscenariosgeneratedby3.11timesand2.O6times，respectively，comparedtotherandomsearch method.TheMOTPEmethodis1.53times beter than TPEintermsofscenarioquality.When combinedwithscenario automaedgenerationandtesting frameworks，thesemethodsefectivelyadress theissueof explodingscenario numbers， allowing for the discovery of scenarios with high testing value.

Key words：Autonomous driving，Scenario generation，Tree-structured Parzen Estimator （TPE），Multi-Objective Tree-structured Parzen Estimator （MOTPE），CARLA

【引用格式】秦琴，楊志勝，李道鑫，等.基于樹結(jié)構(gòu)Parzen估計(jì)器的自動(dòng)駕駛仿真測試關(guān)鍵場景生成方法[J].汽車技術(shù)，2025（5）：39-46.QINQ，YANGZS，LIDX，etal.Automatic Generation Methodof AutonomousDriving SimulationTestScenarios BasedonTree-Structured ParzenEstimator[J].Automobile Technology，2025（5）： 39-46.

1前言

隨著車輛系統(tǒng)復(fù)雜性的提升，交通環(huán)境變化、駕駛?cè)蝿?wù)多樣性等因素成為自動(dòng)駕駛車輛測試評價(jià)面臨的全新挑戰(zhàn)。（剩余11609字）