• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.265-266
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• 2016

본 연구에서는 수집된 자료에서 화물차 교통사고를 분류하고 계절과 기상상태, 도로유형, 법규위반, 사고유형 측면에서 각각의 변수들이 사고 심각도에 미치는 영향을 파악함으로써 유의하게 화물차 교통사고 심각도를 높이는 요인을 분석하고자 하였다. 화물차 사고는 가을의 경우 사고 심각도의 오즈비가 1.23배로 증가하고, 안개가 꼈을 경우 사고 심각도는 16.49배 증가하는 것으로 나타났다. 법규위반, 도로형태, 사고유형 등 여러 요인에 의한 사고 위험도가 증가했지만 특히 도로 외 이탈로 인한 추락사고에서 사고 위험도가 크게 나타났으며 전도전복으로 인한 사고 위험도도 큰 것으로 나타났다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.391-398
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• 2019

In general, truck-involved crashes increase severity in terms of both injury level and crash impact level. Recently, although the frequency and fatality of truck-involved crashes in Korea are rising, their associative studies are very limited. Therefore, the objective of this study is to identify critical factors influencing on injury severity of truck-involved crashes on Korean freeway system. To carry out this objective, this study uses an ordered probit model (OPM) based on a 6-year crash dataset from 2012 to 2017. From the analysis, eight variables were found to have a great effect on injury severity: older driver, crash speed, rear-end collision, number of vehicles involved, drowsy driving, nighttime (0:00 to 6:00) driving, overturn or rollover, and vehicle's fire after crash. However, injury severity was less severe in crashes under snowy condition and crashes to traffic facilities (i.e., crash alone).

• Journal of the Society of Disaster Information
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• v.13 no.4
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• pp.570-576
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• 2017

Trucks take up more portions than cars on highways. Due to this, road use relatively diminish and it serves locally as a threatening factor to nearby drivers. Baggage car accident has distinct characteristics so that it needs the application of different analysis opposed to ordinary accidents. Accident prediction model, one of accident analyses, is used to predict the numbers of accident in certain parts, establish traffic plans as well as accident prevention methods, and diagnose the danger of roads. Thus, this study aims to apply the accident rate of baggage car on highways and calculate the correction factor to be put in the accident prediction models. Accident data based on highway was collected and traffic amounts and accident documents between 2014 and 2016 were utilized. The author developed an accident prediction model based on numbers of annual accidents and set mean annual and daily traffic amounts. This study intends to identify the practical accident prediction model on highway and present an appropriate solution by comparing the prediction model in accords with the accident rate between baggage cars.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.1-15
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• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1105-1113
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• 2013

Understanding the characteristics of truck-involved crashes is of keen interest because such crashes are highly associated with greater potential leading to severer injury. The purpose of this study is to identify factors affecting injury severity of truck-involved crashes on freeways. In addition, a binary logistic regression technique is applied to identify causal factors affecting truck crash severity under normal and adverse weather conditions. Major findings from the analyses are discussed with truck operations strategies including speed enforcement, variable speed limit, and truck lane restriction, from the safety enhancement point of view. The results of this study would be useful for developing traffic control and operations strategies to reduce truck-involved crashes and injury severity in practice.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.122-134
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• 2020

To improve traffic congestion, reduce fuel consumption, and improve the stability of truck operations, truck platooning, in which several trucks are organized in a single platoon, is being actively researched globally. Compared to the operation of a single truck, the operation of a truck platoon requires more caution before the actual operation because an accident of one vehicle in the platoon can lead to an accident with all the vehicles in the platoon. Therefore, this study examined the types of trucks and cargo suitable for truck platooning to prevent safety accidents. The review showed that a closed-van-type truck is appropriate for truck platooning to prevent falling objects during driving. In the case of cargo types, it is necessary to exclude liquids and dangerous goods defined in related laws from truck platooning.

• 도로교통
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• s.94
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• pp.51-64
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• 2003

본 연구는 사고요인과 사고모형의 문헌고찰을 통해 고속도로를 주행하는 버스와 화물차의 사고모형을 개발하고 그 적용방안에 대해 고찰하고자 수행되었다. 고속도로 사고 중 대형차로 인한 차량당 사고율은 승용차보다 월등히 높아 사고의 심각성을 나타내고 있으며, 따라서 이에 대한 별도의 검토가 필요한 시점에 와 있다. 특히 본 연구에 활용된 자료는 비집계된 사상자수로 구간자료를 집합화함으로써 발생하는 문제점을 해소할 수 있다. 모형의 분석기법으로 국내의 경우, 대부분 단순회귀식으로 사고모형을 개발, 적용하여 왔으나 사고수와 사상자수의 특성상 이산적 확률변수로 해석하여 포아송분포와 음이항분포로 적용하는 것이 바람직하다. 따라서 본 연구에서는 버스와 화물차의 사고유형별로 적합한 사고 모형을 개발하여 이로 인한 인사사고 요인에 대한 영향을 분석하고 그 적용방안을 제시하였다. 이러한 연구는 도로설계, 운영, 교통법규, 교통행정 등의 분야에서 거시적인 정책적 방향성을 제시하리라 판단된다. 특히 본 연구는 고속도로 운영주체인 한국도로공사의 고속도로사고조서를 바탕으로 사고유형별 사고모형을 개발, 적용한 것으로 고속도로의 안정성 향상을 위한 제반 정책 수립에 기초자료로 활용될 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.253-255
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• 2021

경찰청 자료에 따르면 한국에서 사망 교통 사고의 75.5%는 화물차 사고이다. 한국에서 화물차 사고로 숨지는 사람은 매년 약 1000명이며, 매일 2~3명이 화물차 사고로 사망한다. 한국의 화물노동자들은 화물차 사고가 끊이지 않는 이유로 열악한 노동조건을 응답하고 있다. COVID 19는 비대면 물류 수요를 증가시키고 있다. COVID 19로 인하여 급격하게 증가한 물류 수요는 기존의 낙후된 물류 기술과 낙후된 물류 시스템으로 인하여 운송 과정의 비효율성을 나타내고 있다. 이러한 한국 운송 시스템의 비효율성은 영세 물류 개인 사업자들에 대한 과도한 업무 부담으로 이어지고 있으며, 한국 운송 시스템의 비효율성은 2020년 이후 급격하게 증가한 물류 산업 재해 사망자 수로 나타나고 있다. CIPs에 입주한 한국 중소 기업들은 별도의 스마트 출입 인증 시스템을 갖추지 못하고 있는 경우가 많으며, 이로 인하여 최종 목적지인 출입 단계에서 많은 운송 시간들이 낭비되고 있다. 스마트 출입 인증 시스템 아키텍쳐를 통하여 영세 물류 개인 택배 사업자는 법적 안정성 개선 효과를 얻을 수 있으며, CIPs 중소 기업들은 물류 운송 시간을 단축하는 효과를 얻을 수 있다. CIPs스마트 출입 시스템은 현재 활성화되어 있는 Mobile OTP를 활용하므로, 시스템 설계 비용을 크게 절감할 수 있으며, 개별 휴대폰 단말기에 발생하는 Data용량 부담을 크게 줄이고, 개별 휴대폰 단말기의 응답 속도를 개선할 수 있다. 또한 기존에 다양하게 활용되던 OTP 체계와 호환성이 있으며, OTP 시스템의 오랜 사용 기간을 통한 시스템 신뢰성도 높다. 사용자 고객들의 OTP 시스템 이해도도 다른 스마트 출입 시스템에 비하여 높다.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.119-127
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• 2012

For traffic safety, it is imperative for motorists to secure their clear view and to maintain a similar speed with others while driving in a lane. Large-sized vehicles at lower speeds, however, are likely to increase the risk of accident when they share a lane with cars. Although to overcome this complication the Korean Road Traffic Act established rules for the safe use of roads, the reality is that the rules are seldom observed strictly. In this light, this study was designed to analyze the severity of truck-involved accidents, thereby providing justification for the need of truck-designated lanes and thus contributing to measuring road safety more precisely. A binomial logistic regression model was applied to analyze the severity of truck-involved accidents. The analysis showed that several variables affect the severity of truck-involved accidents on freeways; i.e., violation against the rule of truck-designated lanes, weather, difference between daytime and nighttime, and parking on road shoulder. Moreover, the strong enforcement will be needed to make motorists observe the rule, because a Wald statistical test showed that the violation against the rule of truck-designated lanes has the largest influence on the severity.