ScholarWorks@Hanyang University ERICA Campus: Park, June young

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Park, June young (박준영)

COLLEGE OF ENGINEERING SCIENCES (DEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING)

Research Area: 교통물류

Tel 031-400-5151
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traffic safety:8||교통안전:7||Traffic safety:7||고속도로:5||AHP:5||safety:4||traffic engineering:4||driving simulator:4||안전성능함수:4||autonomous vehicle:3||COVID19:3||kansei engineering:3||Machine learning:3||Safety performance function:3||Safety:3||transport management:3||VISSIM:3||sustainability:3||expressway:3||XAI:3||CAV:2||LSTM:2||geographic information system:2||자율주행버스:2||accident analysis:2||port safety:2||Crash modification factor:2||Highway:2||traffic safety warning information:2||지리정보시스템:2||crash severity analysis:2||transportation safety:2||quantification theory typeⅠ model:2||사고 심각도:2||crash severity model:2||사고 예측:2||항만 안전:2||random forest:2||ROADWAYS:2||data and data science:2||data mining:2||Logistic regression:2||Traffic data:2||road & highways:2||Fog:2||Random forest:2||감성공학:2||강화학습:2||big data:2||DQN:2||ARIMA:2||Generalized nonlinear models:2||safety performance function (SPF):2||Crash risk:2||semantic differential method:2||군집분석:2||Port safety:2||VTMICRO Model:2||Gradient boosting:2||correlation analysis:2||spatial heterogeneity:2||Accident risk management algorithm:2||Ensemble model:1||Explainable artificial intelligence:1||Expressway:1||Expressway weaving segments:1||Extreme gradient boosting:1||FRAMEWORK:1||Freight routes:1||Freight truckinvolved crash:1||Freight vehicle:1||Geographic information system:1||Headup display:1||Heterogeneity:1||Hexagonal grid:1||Hipass:1||Hurdle beta regression model:1||Infraguidance:1||Injury severity:1||Internet of Things (IoT):1||Inversegaussian:1||Kansei engineering:1||Korea:1||Korean ports:1||LEVEL:1||Lateral deviation:1||Lateral safety assessment:1||Logistic Regression Model:1||Lowering the speed limit:1||MARS:1||METAANALYSIS:1||MODELS:1||MULTIPLE TREATMENTS:1||Machine Learning:1||Marijuana:1||Maximum length:1||Medical legalization:1||Metaanalysis:1||Mobility:1||Multicriteria Decision Making:1||Multilevel Bayesian logistic regression model:1||Negative binomial:1||Negative binomial regression:1||Neural network:1||Nonsignalized Intersection:1||Nonmotorized traffic safety:1||PREDICTION:1||Pedestrian safetyLag timeCopula structureBinary logitOrdered logit:1||Personal mobility:1||Port worker:1||Port worker safety:1||Predictive models:1||Probabilistic model:1||Public transportation:1||RATES:1||REGRESSION:1||Random effect:1||Random effects models:1||Random parameter:1||Random parameters:1||Random parameters models:1||Realend risk algorithm:1||Realtime crash analysis:1||Realtime crash prediction:1||Realtime fog warning system:1||Realtime locating system:1||Realtime risk assessment:1||Realtime traffic data:1||Rearend collision risk:1||Rearend crash:1||Recreational legalization:1||Reduced visibility conditions:1||Rest area:1||Risk Avoidance Behavior:1||Road Policy:1||Road safety countermeasures:1||Road traffic safety:1||Roads:1||Roadway segments:1||SAFETY:1||SEGMENTS:1||SEVERITY:1||Safety Guidance Strategy:1||Safety Performance Function:1||Safety analysis:1||Safety effectiveness:1||Safety effects:1||Safety indicators:1||Safety performance:1||Safety performance analysis:1||Safety performance functions (SPFs):1||Scheduling:1||Shoulder and lane widths:1||Signalized intersection:1||Signalized intersections:1||Speed adjustment:1||Speed management:1||Speed stability:1||Surrogate Safety Measure:1||Surrogate safety:1||Sustainable forest management:1||Sustainable transportation:1||TIME:1||TTC:1||Time of purchase:1||Traffic Flow Control Algorithm:1||Traffic Indicator:1||Traffic Optimization:1||Traffic conflict measures:1||Traffic crashes:1||Traffic fatalities:1||Traffic flow optimization:1||Traffic simulation:1||Traffic violation:1||Traffic volume:1||Trumpet ramp:1||Twostage residual inclusion:1||URBAN ARTERIALS:1||Urban arterials:1||Urban road:1||Urban roads:1||VSL(가변속도제한):1||Variable Speed Limit:1||Vulnerable areas:1||Weather data:1||Work Zone:1||accident severity:1||advanced warning information system (AWIS):1||agricultural land:1||agroforestry:1||arterial:1||artificial intelligence:1||augmentation:1||autonomous bus:1||autonomous vehicle collision report:1||bayesian latent class:1||bivariate probit model:1||black box:1||calibration:1||carfollowing:1||chevron marking:1||climate change safety & hazards traffic engineering UN SDG 13: Climate action Your access options:1||clustering:1||combination factors:1||connected vehicle:1||control algorithm:1||cooperated intelligent transportation system (CITS):1||countermeasures:1||crash analysis:1||crash avoidance:1||crash data:1||crash frequency model:1||crash hotspot:1||crash modification factor (CMF):1||crash prediction:1||crash prediction model:1||crosssectional method:1||data analytics:1||digital tachograph:1||distance halo effect:1||driver compliance:1||driving behavior:1||driving behaviour:1||driving big data:1||driving safety:1||drone data:1||ecosystem service:1||effect size:1||empirical bayes:1||enforce system:1||evaluation:1||exclusive bus lane:1||extreme gradient boosting (XGB):1||farm forestry rules:1||farmers' perception:1||farmland trees and forests:1||forest products:1||freeway facility types:1||freight vehicle:1||hierarchically structured design:1||highway:1||highway safety manual:1||highway safety manual (HSM):1||image recognition algorithm:1||invehicle dashcam video data:1||invehicle information design:1||individual tendency:1||integrated crash risk:1||interrupted urban road:1||intersection:1||inverse distance weighted interpolation:1||kernel density estimation:1||land transports:1||latent class model:1||lateral safety:1||level of safety:1||livelihoods:1||low visibility:1||machine learning:1||managed lane:1||marginal effect:1||markov decision process:1||meta analysis:1||microlevel hotspot:1||microtraffic simulation:1||mixed traffic:1||motorized and nonmotorized crashes:1||multicriteria decisionmaking:1||multilevel model:1||multiplevehicle accidents:1||multivariate adaptive regression splines:1||negative binomial model:1||net promoter score:1||network screening:1||observational beforeafter study:1||open road tolling:1||pavement marking:1||private sector data:1||probability of rearend crash:1||probability of seriously injured:1||promising driving behavior indicator:1||public transportation:1||random effect:1||random effects Poisson inverse Gaussian:1||realtime data:1||realtime monitoring:1||rearend crash:1||reinforced learning:1||reinforcement learning:1||right turn:1||risk factor:1||road accident analysis:1||roads & highways:1||roundabout:1||safety & hazards:1||safety Evaluation:1||safety assessment:1||safety effects:1||safety indicators:1||safety vulnerable sections:1||school zone:1||secondary crashes:1||severe crash:1||severity:1||severity model:1||shared personal mobility:1||signalized intersection:1||simulatorbased driving behavior:1||speed limit:1||speed reduction:1||speed stability:1||sustainable road safety:1||text mining:1||time to collision:1||timeseries analysis:1||traffic conflict:1||traffic crash severity:1||traffic incident management:1||traffic simulation:1||transportation management:1||travel mode choice:1||tree and forest resources:1||trees on farms:1||truck safety:1||urban intersections:1||urban road traffic management:1||urban traffic safety:1||value score:1||variable speed limit:1||vehicle trajectory data:1||virtual road safety audits:1||wider lane line width:1||가변형 속도제한시스템 adverse weather:1||갈매기 노면표시:1||거리 후광 효과:1||경험적 베이즈 방법론:1||공간적 이질성:1||공사구간:1||공유 개인형 이동수단:1||관측적 사전사후 분석 방법론:1||교통 상충:1||교통 시뮬레이션:1||교통데이터:1||교통류 최적화:1||교통안전 경고정보:1||교통안전대책:1||교통안전성:1||기상 데이터:1||노면표시:1||능동적 안전관리 시스템:1||다기준 의사결정:1||대체안전지표:1||데이터 마이닝:1||도로안전편람(HSM):1||도심부 도로:1||도심부 인프라:1||동적 교통류:1||드론 데이터:1||딥러닝:1||랜덤포레스트:1||마코브 디시젼 프로세스:1||머신러닝:1||미시교통류시뮬레이션:1||버스전용차로:1||베이지안 잠재 계층분석:1||변수 이질성:1||복합 영향요인:1||블랙박스:1||블랙박스 영상:1||빅 데이터:1||빅데이터:1||사고 분석:1||사고 심각도 모형:1||사고 핫스팟:1||사고수정계수(CMF):1||사고심각도 분류분석:1||사고심각도 분석:1||사고예측모형:1||사고위험 알고리즘:1||사물인터넷:1||상관분석:1||세부위험구역:1||속도감소:1||수량화Ⅰ류 이론:1||스케줄링:1||시계열 분석:1||신호 교차로:1||실시간사고위험평가:1||실시간위치추적 시스템:1||심각 사고:1||심각도:1||심각한 상해발생 확률:1||악천후 기상 조건:1||안전성:1||안전성 취약 구간:1||안전성 평가:1||안전성능함수(SPF):1||역가우스:1||역거리가중치보간법:1||연평균 1시간 교통량:1||연평균 일교통량:1||영상인식 알고리즘:1||운전자 순응도:1||운전자 주행행태:1||위험행동 회피 알고리즘:1||음이항:1||음이항 회귀:1||의미미분법:1||이동성 Bus Dedicated Lane:1||익스트림 그래디언트 부스팅:1||인프라 가이던스:1||임의 효과:1||임의효과:1||자율주행 이동 로봇:1||자율주행차:1||자율주행차 사고 보고서:1||자율차:1||자율협력주행:1||전용차로:1||제어 알고리즘:1||제한속도 하향:1||주행 빅데이터:1||주행 시뮬레이터:1||차량 추종:1||차선폭원 두께변화:1||커널밀도추정:1||텍스트마이닝:1||통합사고위험도:1||트럼펫형 램프:1||하이패스:1||항만 근로자 안전:1||화물운송경로:1||화물차:1||회전교차로:1||횡방향 안전성:1||횡방향 안전성 평가:1||횡방향 편차:1||후미추돌 사고발생 확률:1||ACCIDENT MODIFICATION FUNCTIONS:1||후미추돌사고:1||AI technologies:1||Accident prediction model:1||Accident severity:1||Accidents:1||Active safety management system:1||Active traffic management:1||Algorithm verification:1||Analytic Hierarchy Process:1||Analytical models:1||Annual average daily traffic:1||Artificial Intelligence:1||Audio warning:1||Autonomous Bus:1||Autonomous Mobility Robot:1||Autonomous vehicles:1||Average hourly traffic:1||Battery electric vehicles:1||Bayesian multilevel Poissonlognormal joint model:1||Bicycle lanes:1||Big data:1||Black box:1||Bluetooth detection system:1||Bus demand forecasting:1||CRASHFREQUENCY:1||Calibration method:1||Cannabis:1||Cluster analysis:1||Collision Avoidance Algorithm:1||Conflict Prediction:1||Connected Autonomous Vehicle:1||Connected vehicle and automated vehicle technologies:1||Consumer intention:1||Container port:1||Cooperative autonomous driving:1||Corridor analysis:1||Crash Prediction:1||Crash avoidance:1||Crash data:1||Crash modification factors:1||Crash modification factors (CMFs):1||Crash risk hotspot:1||Crash risk prediction model:1||Crash severity model:1||Crosssectional method:1||Data augmentation:1||Data mining:1||Data models:1||Decision support:1||Decision tree model:1||Decriminalization:1||Deep learning:1||Deep neural network (DNN):1||Demand responsive transit:1||Discrete choice model:1||Driver's Usual Driving Characteristics:1||Driving behavior event data:1||Driving simulator:1||Dynamic Traffic Flow:1||EXPOSURE:1||Endogeneity:1||Ensemble:1||

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