驾驶风险监测与干预技术研究综述
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Review on driving risk monitoring and intervention technologies
LI Guofa ，OUYANG Delin2，CHEN Chen1，NIE Binging1，ZHANG Wei2，YU Huili4， Liu Bin5， ZHANG Qiang26，WANG Wenjun1，CHENG Bo1，3，LI Shengbo*1
（1.SchoolofVehicleandMobility，TinghaUniversity，Beijingoo084，China；2.CollgeofMechanicaland VehicleEngineering，ongqingUniersity，hongqing4，ina；3.uzouAutomoiveResearchte TsinghuaUniversityhou5，ina；4.ongqinganganutomobileCo.td，hongqing4，i； 5.China FAW Group Corporation R&D Institute，Changchunl3ooo0，China； 6.China Automotive Engineering Research InstituteCo.，Ltd，Chongqing 4122，China.）
Abstract：Safety hasalways beenacrticalconcern inroad transportation，servingasafundamental pilar for ensuringtrafic eficiencyand supporting economic development.Driving riskmonitoring and interventionare key technologies forenhancing vehiclesafety，particularlywithadvancements inperceptionand informationtechnology， which providearobustdata foundationand newavenues for implementation.This paper systematicall reviews theresearchprogressofdrivingriskmonitoringandinterventiontechniques.Firstlyitexaminesthecurentstateof drivingriskmonitoringfrombothofin-vehicleandexternalperspectives.Secondly，itreviews interventionstrategies frombothoflineandonlineapproaches.Studieshaveshownthatinterventionsintegratingvisualauditoryandaptic feedbackcansignificantlyimprove driver response times，while hapticwarning systemscan helpreduce therateof drivererrors.Thenitisexploredthat theintegrationofriskmonitoringandinterventiontechnologiesintoAdvanced DriverAssistance Systems （ADAS），autonomousdrivingsystems，connectedvehiclesystems，andautomateddriing platforms.Studies have shown that inteligentsystems basedonvehicle-road-cloud collaborationcanimprove the real-timeperformanceofriskwarnings.TheapplicationofADAShasbeenproveneffectiveinreducing traficaccident ratesand lowering Usage-Based Insurance（UBl） lossratios.Finaly，futureresearch directionsarediscussed， including modeloptimizationforlightweightdeployment，bigdataapplications，cloud-basedcontrolplatforms，and the role of large-scale autonomous driving models inadvancing risk monitoring and intervention technologies.
Keywords：autonomous driving；riskmonitor；risk intervention；driving safety； vehicle-road-cloud integration
道路交通安全是全球范围内一项重大的公共健康问题，世界卫生组织发布的《2023年全球道路安全现状报告》中指出，2021年全球约有119万人因道路交通事故死亡[1。（剩余36661字）