• 대한교통학회지
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• 제27권3호
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• pp.91-102
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• 2009

도로설계 안전성을 평가하기 위해서는 도로의 설계 요소변화가 사고에 미치는 영향을 예측할 수 있어야 한다. 이를 위해 본 연구에서는 통계적 방법, 사고이력, 전문가의 판단, 그리고 기존문헌고찰 등 다양한 방법을 통하여, 설계요소의 특징과 사고율 및 사고빈도의 관계를 반영할 수 있는 AMF(Accident Modification Factor)를 개발하고자 하였다. 본 연구에서는 AMF를 좌회전전용차로, 우회전전용차로, 시거, 교차각 등의 항목을 대상으로 개발하였다. 개발된 AMF를 적용한 경우의 사고 예측값, 사고예측모형을 통한 예측값을 실제 사고데이터와 비교분석함으로써 적정성을 검토하였다. 분석결과, AMF를 적용한 예측값이 사고예측모형을 통한 예측 값보다 예측력이 우수함을 확인할 수 있었다. 이러한 결과는 사고를 예측함으로써 도로설계 안전성을 평가하는 알고리즘에 있어 AMF가 도로의 설계요소의 특성을 보다 효과적으로 반영하며, 지방부 교차로에서 각각의 해당요소가 사고에 미치는 영향을 판단할 수 있는 지표가 될 수 있음을 의미한다.

• 한국도로학회논문집
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• 제17권3호
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• pp.133-141
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• 2015

PURPOSES : This study dealt with traffic accidents occurring within roundabouts. The objective of this study was to analyze safety effect by introduction of roundabouts. METHODS : In pursuing the above, traffic accident data on roundabouts are collected and compared. For the analysis, collected data were separated as all intersection points, turning lane accident, approach lane accident by geometric design. RESULTS : Through the study results, it was found that the total accidents decreased by 55 accidents/2 year with safety effect of roundabouts. Also the result shows that accidents by point of two-lane roundabout at turning lane(0.26) and approach lane(0.27) is risky than total accidents by point(0.09). Moreover, accidents by point shows high value as diameter of a roundabout is bigger. CONCLUSIONS : When a roundabout is introduced at the intersections there are safety effects by reduction of traffic accidents.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.262-265
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• 2008

We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

• 한국ITS학회 논문지
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• 제17권3호
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• pp.87-97
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• 2018

교통사고 관련 제보는 비정형 데이터로서 교통사고를 유발한 가해자나 피해자의 관점이 아닌, 교통사고 발생 지점과 구간, 시간대에 있었던 타 운전자의 관점에서 생성된 교통정보의 가치를 가지고 있다. 그러나, 비정형 데이터인 교통제보가 빅 데이터로서 교통사고 통계나 교통관련 연구에 활용되지 못하였으나, 텍스트 마이닝 기법을 활용한 본 연구를 통해 비정형의 빅 데이터를 시각화하고 해석하여, 기존의 정형 데이터에서 분석하지 못한 정보를 도출할 수 있었다. 그리고 교통사고 발생으로 인한 도로상 영향을 파악할 수 있었다. 이러한 분석으로 교통제보의 트랜드를 파악하고, 운전자가 제보하는 "도로명", "지점명", "시간대"를 추출하였으며, 교통사고 발생으로 다른 운전자에게 가장 많은 영향을 미치는 지점과 구간의 파악이 가능하였다. 향후 실제 교통사고 데이터와 결합하여 교통제보와의 상관성 분석 등을 통해 비정형 데이터의 활용방안을 모색할 계획이다.

• 디지털정책학회지
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• 제2권4호
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• pp.1-10
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• 2023

본 연구는 경찰교통에서의 효과적 ChatGPT 활용 방안 도출을 위한 사전 연구로서 운전면허 학과시험과 도로교통사고감정사 시험에 대한 ChatGPT의 응답을 분석하였다. ChatGPT가 뛰어난 성능과 접근성으로 여러 분야에서 기대를 받고 있으나 경찰 교통법규와 같이 고도의 정확성이 요구되는 분야에서는 사전에 그 성능과 한계를 탐색할 필요가 있다. 이에 본 연구에서는 운전면허 학과시험 문제은행과 도로교통사고감정사 1차 시험을 대상으로 파이썬 코드로 OpenAI API를 이용해 30회의 반복 실험으로 ChatGPT의 응답을 수집하고 응답 결과를 바탕으로 시험별·연도별·내용 영역별 정답률, 일관성 능력을 분석하였다. 분석 결과 첫째, 운전면허 학과시험 및 도로교통사고감정사 1차 시험의 평균 정답률은 각 44.60%, 35.45%로 합격기준보다 낮았다. 연도별로는 2022년 이후 정답률이 평균 정답률을 하회했다. 둘째, 영역별 정답률은 29.69%~56.80%로 나타나 큰 편차를 보였다. 셋째, 정답을 맞힌 경우 95% 이상 일관되게 같은 응답을 출력하였다. ChatGPT의 효과적 활용을 위해서는 사용자의 전문 지식, 평가 데이터 및 방법 마련, 양질의 교통법규 말뭉치 설계와 주기적 학습이 필요하다고 판단된다.

• 한국안전학회지
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• 제29권5호
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.

• 자동차안전학회지
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• 제10권1호
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• pp.27-31
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• 2018

This paper reports an analysis of cyclist accident cases with respect to passenger vehicles on Korean roads. A typology based on Initiative for the Global Harmonization of Accident Data (iGLAD) code book is applied to a traffic accident analysis system(TAAS), which has the real-world crash data on Korea roads, to understand the accident scenarios in more detail and efficiently. Similarly this typology has been used for Germany In-Depth Accidents Study (GIDAS) as well. The accident data analysis with consideration of the typology of Korean road conditions may prioritize traffic safety issues regarding cyclists and is aimed to develop an Automatic Emergency Braking (AEB) system for cyclist. In summary, this paper characterizes and analyzes the scenarios of cyclist crashes with passenger car. The most common accident scenarios on Korean roads are Car-to-Bicyclist Nearside Adult (CBNA) and Car-to-Bicyclist Longitudinal Adult (CBLA), which are more than 86% of total accidents cases. Therefore, it is inferred that AEB cyclist system should include these accident types in the operational design domain to reduce more fatality in Korea.

• 한국도로학회논문집
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• 제17권6호
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• 한국도로학회논문집
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• 제17권6호
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• pp.85-95
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• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

• 한국도로학회논문집
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• 제16권3호
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• pp.101-107
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• 2014

PURPOSES : This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS : To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS : The optimal model for pedestrian accidents is evaluated to be Tobit model.