• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.63-82
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• 1995

This paper deals with the forecasting model for traffic accident. Its objective is to develop the appropriate model to project the accident of Chung-Chong Region. Two types of models between motorization (M) and personal hazard (P) are tested : One is inverted-U (bell type) curve and the other is increasing (or decreasing) curve. The statiscal and sensitivity analyses show that exponential model (type III) and multiplicative model (type II) are well fit to the given cross-sectional and time-series accident data. The model projects that the fatality per 100, 000 persons of Chung-Chong region, when the motorization level (M) is 0.2, would be in the range between 18 and 77 persons. The paper concludes that the accident level is the function of motorization and the result of implementing the safety policy of a region.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.64-75
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• 2017

Previous count models using fixed parameter can not consider the unobserved heterogeneity, as the standard error of the count value is underestimated, excessive t-values are derived thereby reducing the reliability of the model. Also, the study of unsignalized intersections are inadequate because of the difficulty of collecting data and statistical limits for accurate analytical processes compared to the signalized intersections. The purpose of this study is to analyze the factors affecting traffic accidents by constructing the count model using random parameters, and it aimed to distinguish between existing studies based on the rural unsignalized intersections. As a result of the analysis, 7 variables were presented as significant variables, and 2 variables(presence of crosswalk, speed limit) were presented as random parameter.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.207-214
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• 2009

This study proposed an advanced warning information system based on real-time traffic conflict analysis. An algorithm to detect and analyze unsafe traffic events associated with car-following and lane-changes using individual vehicle trajectories was developed. A positive guidance procedure was adopted to provide warning information to alert drivers to hazardous traffic conditions derived from the outcomes of the algorithm. In addition, autoregressive integrated moving average (ARIMA) analyses were conducted to investigate the predictability of warning information for the enhancement of information reliability.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.47-56
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• 2003

There are no specific criteria deciding what type of crosswalk installs although 4 typed crosswalks at signalized intersections classify according to number of stop line, spacing from the border of intersections and existence of traffic islands or not. Accidents involving pedestrians at signalized intersections are classified by type of crosswalks by traffic volume, pedestrian volume at crosswalk, intersection geometry and phase in view of pedestrians' safety at 50 intersections in Gwangju. The Multiple regression models are applied to express the pedestrian accident rate. In addition, process deciding what type of crosswalk installs which includes accident rate involved pedestrian is changed into number of accident is represented to reduce number of accidents. This paper presents what type of crosswalk installs in order to reduce pedestrian involved accidents at new or existing crosswalk.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.157-164
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• 2012

Road signs serve guide informations for efficient traffic control and are regulated by Road Sign Regulation. But few road managers break the regulation because of civil complaint and cause driver's confusion. Also, as promote the road name guide signs and the new road signs on expressway, the driver's confusion being increased. This study analysis factors of driver's confusion, calculates limited information on road signs and specifies modes of driver's confusion caused by road signs. The traffic accident data during 3 years is calculated in order to see how much intimate connection between the road sign confusion and the traffic.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.133-144
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• 2004

A model and a measure which can evaluate the risk of rear end collision are developed. Most traffic accidents involve multiple causes such as the human factor, the vehicle factor, and the highway element at any given time. Thus, these factors should be considered in analyzing the risk of an accident and in developing safety models. Although most risky situations and accidents on the roads result from the poor response of a driver to various stimuli, many researchers have modeled the risk or accident by analyzing only the stimuli without considering the response of a driver. Hence, the reliabilities of those models turned out to be low. Thus in developing the model behaviors of a driver, such as reaction time and deceleration rate, are considered. In the past, most studies tried to analyze the relationships between a risk and an accident directly but they, due to the difficulty of finding out the directional relationships between these factors, developed a model by considering these factors, developed a model by considering indirect factors such as volume, speed, etc. However, if the relationships between risk and accidents are looked into in detail, it can be seen that they are linked by the behaviors of a driver, and depending on drivers the risk as it is on the road-vehicle system may be ignored or call drivers' attention. Therefore, an accident depends on how a driver handles risk, so that the more related risk to and accident occurrence is not the risk itself but the risk responded by a driver. Thus, in this study, the behaviors of a driver are considered in the model and to reflect these behaviors three concepts related to accidents are introduced. And safe stopping distance and accident occurrence probability were used for better understanding and for more reliable modeling of the risk. The index which can represent the risk is also developed based on measures used in evaluating noise level, and for the risk comparison between various situations, the equivalent risk level, considering the intensity and duration time, is developed by means of the weighted average. Validation is performed with field surveys on the expressway of Seoul, and the test vehicle was made to collect the traffic flow data, such as deceleration rate, speed and spacing. Based on this data, the risk by section, lane and traffic flow conditions are evaluated and compared with the accident data and traffic conditions. The evaluated risk level corresponds closely to the patterns of actual traffic conditions and counts of accident. The model and the method developed in this study can be applied to various fields, such as safety test of traffic flow, establishment of operation & management strategy for reliable traffic flow, and the safety test for the control algorithm in the advanced safety vehicles and many others.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.133-144
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• 2017

Recently, weather information is getting closer to our real life, and it is a very important factor especially in the transportation field. Although the damage caused by the abnormal climate changes around the world has been gradually increased and the correlation between the road risk and the possibility of traffic accidents is very high, the domestic research has been performed at the level of basic research. The Purpose of this study is to develop a risk map for the road hazard forecasting service of weather situation by linking real - time weather information and traffic information based on accident analysis data by weather factors. So, we have developed a collection and analysis about related data, processing, applying prediction models in various weather conditions and a method to provide the road hazard map for national highways and provincial roads on a web map. As a result, the road hazard map proposed in this study can be expected to be useful for road managers and users through online and mobile services in the future. In addition, information that can support safe autonomous driving by continuously archiving and providing a risk map database so as to anticipate and preemptively prepare for the risk due to meteorological factors in the autonomous driving vehicle, which is a key factor of the 4th Industrial Revolution, and this map can be expected to be fully utilized.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1255-1263
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• 2021

While it could become an alternative water resource, fog could undermine traffic safety and operational performance of infrastructures. To reduce such adverse impacts, it is necessary to have spatially continuous fog risk information. In this work, tree-based machine-learning models were developed in order to quantify fog risks with routine meteorological observations alone. The Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGB), and Random Forests (RF) were chosen for the regional fog models using operational weather and visibility observations within the Jeollabuk-do province. Results showed that RF seemed to show the most robust performance to categorize between fog and non-fog situations during the training and evaluation period of 2017-2019. While the LGB performed better than in predicting fog occurrences than the others, its false alarm ratio was the highest (0.695) among the three models. The predictability of the three models considerably declined when applying them for an independent period of 2020, potentially due to the distinctively enhanced air quality in the year under the global lockdown. Nonetheless, even in 2020, the three models were all able to produce fog risk information consistent with the spatial variation of observed fog occurrences. This work suggests that the tree-based machine learning models could be used as tools to find locations with relatively high fog risks.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1040-1046
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• 2005

지능형교통시스템(Intelligent Transportation System: ITS)의 기술발전에 따라 고속도로 상에도 각종 검지 센서가 설치되고 교통정보가 다양한 형태로 제공되고 있으며, 전자요금징수시스템(Electronic Toll Collection System: ETCS) 또한 시범운영단계를 마치고 모든 고속도로를 대상으로 확대적용을 준비 중에 있다. 본 논문에서는 ITS 관련시스템 중 고속도로를 대상으로 적용되는 전자요금징수시스템과 유고관리 시스템을 대상으로 수행되었던 시뮬레이션 사례를 소개하고, ITS 분야에서의 시뮬레이션 적용 필요성에 대해서 논의하고자 한다. 전자요금징수시스템을 대상으로 한 시뮬레이션의 경우 현재 시범운영중인 영업소를 대상으로 향후 다양한 요금지불수단 도입에 따른 효과적인 영업소 운영방안을 도출하는 것을 목적으로 개발되었으며, 운전자들의 영업소 차로선택모형 등에 대한 사전연구를 통하여 모델링에 반영하였다. 또한, 고속도로 유고관리시스템의 경우 사고 직후 사고영향에 대한 실시간 시뮬레이션을 수행하여 지체지속시간 및 지체영향구간을 예측하여, 향후 교통정보제공에 활용하는 것을 목적으로 개발되었다. 개발된 시뮬레이션 모델을 통하여 각종운영방안에 대한 평가를 수행하였으며, 실제 유고상황에서의 검지자료와의 비교를 통하여 성능평가를 수행하였다.

• Journal of the Korean Regional Science Association
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• v.11 no.1
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• pp.21-30
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• 1995

This paper deals with the forecasting models for traffic accident by region. Its objectives are to develop the appropriate model for projecting the accident and to analyze the regional characteristics of the accident model. The main results are as follow. First, the literature review, statistical tests and sensitivity analyses show that the joint model combined both PTM and Exponential functions is appropriate to project the traffic accidents by region. Second, the statistical analyses by region. Second, the statistical analyses on the regional accident models indicate that the levels of significance in terms of t-value, $R^2$ and F-value are very high. Finally, the comparative analyses among regions show that the regional differences on the accident patterns can be explained by the joint models and the accident indices (parameters, $P_{max}$, 1/b, $\eta$ etc.) of each region.