PURPOSES : This study aimed to identify factors affecting the duration of traffic incidents in tunnel sections, as accidents in tunnels tend to cause more congestion than those on main roads. Survival analysis and a Cox proportional hazards model were used to analyze the determinants of incident clearance times. METHODS : Tunnel traffic accidents were categorized into tunnel access sections versus inner tunnel sections according to the point of occurrence. The factors affecting duration were compared between main road and tunnel locations. The Cox model was applied to quantify the effects of various factors on incident duration time by location. RESULTS : Key factors influencing mainline incident duration included collision type, driver behavior and gender, number of vehicles involved, number of accidents, and post-collision vehicle status. In tunnels, the primary factors identified were collision type, driver behavior, single vs multi-vehicle involvement, and vehicles stopping in the tunnel after collisions. Incidents lasted longest when vehicles stopped at tunnel entrances and exits. In addition, we hypothesize that incident duration in tunnels is longer than in main roads due to the reduced space for vehicle handling. CONCLUSIONS : These results can inform the development of future incident management strategies and congestion mitigation for tunnels and underpasses. The Cox model provided new insights into the determinants of incident duration times in constrained tunnel environments compared to open main roads.

PURPOSES : This study investigates the factors affecting extra-long tunnel accidents by integrating data on tunnel geometry, traffic flow, and traffic accidents and derives the underlying implications to mitigate the severity of accidents. METHODS : Two processes centered on three key data points (tunnel geometry, traffic flow, and traffic accidents) were used in this study. The first is to analyze the spatial characteristics of extra-long tunnel traffic accidents and categorize them from multiple perspectives. The other was to investigate the factors affecting extra-long tunnel traffic accidents using the equivalent property-damage-only (EPDO) of individual accidents and the aforementioned data as the dependent and independent variables, respectively, by employing an ordered logistic regression model. RESULTS : Gyeonggi-do, Gyeongsangnam-do, and Gangwon-do are three metropolitan municipalities that have a significant number of extra-long tunnel accidents; Busan and Seoul have the most extra-long tunnel accidents, accounting for 23.2% (422 accidents) and 18.6% (339 accidents) of the 1,821 accidents that occurred from 2007 to 2020, respectively. In addition, approximately 70% of extra-long tunnel traffic accidents occurred along tunnels with lengths of less than 2 km, and Seoul and Busan accounted for over 60% of the top 20 extra-long tunnels with accidents. Most importantly, the Hwangryeong (down) tunnel in Busan experienced the most extra-long tunnel traffic accidents, with 77 accidents occurring during the same period. As a result of the ordered logistic regression modeling with EPDO and multiple independent variables, the significant factors affecting the severity of extra-long tunnel traffic accidents were determined to be road type (freeway, local route, and metropolitan city road), traffic flow (speed), accident time (year, summer, weekend, and afternoon), accident type (rear end), traffic law violations (safe distance violation and center line violation), and offending vehicles (van, sedan, and truck). CONCLUSIONS : Based on these results, the following measures and implications for mitigating the severity of extra-long tunnel traffic accidents must be considered: upgrading the emergency response level of all road types to that of freeways and actively promoting techniques for regulating high-speed vehicles approaching and traversing within extra-long tunnels are necessary. In addition, the emergency response and preparation system should be reinforced, particularly when the damage from extra-long tunnel traffic accidents is more serious, such as during the summer, weekends, and afternoons. Finally, traffic law violations such as safe distance and centerline violations in extra-long tunnels should be prohibited.

This paper attempted to analyze the correlation between the risk image of the evacuees in the tunnel and the variables that affect the evacuation behavior due to the closed feeling. As to whether there is a difference in the level of recognizing the tunnel risk image according to the distribution of jobs, the null hypothesis was rejected at the significance probability of 0.002, so it can be said that the level of recognition of the tunnel risk image varies depending on the job group. In the distribution difference between gender and tunnel risk image recognition level, the significance probability was 0.012, indicating that the null hypothesis was rejected, indicating that the tunnel risk recognition distribution according to gender was different. As a result of analyzing the distribution difference between the tunnel's closed feeling and the tunnel risk perception level, the significance probability was 0.001, and the null hypothesis was rejected, indicating that there was a difference in the tunnel risk image level.

PURPOSES : In this study, the factors affecting the severity of traffic accidents in highway tunnel sections were analyzed. The main lines of the highway and tunnel sections were compared, and factors affecting the severity of accidents were derived for each tunnel section, such as the tunnel access zone and tunnel inner zone. METHODS : An ordered probit model (OPM) was employed to estimate the factors affecting accident severity. The accident grade, which indicates the severity of highway traffic accidents, was set as the dependent variable. In addition, human, environmental, road condition, accident, and tunnel factors were collected and set as independent variables of the model. Marginal effects were examined to analyze how the derived influential factors affected the severity of each accident. RESULTS : As a result of the OPM analysis, accident factors were found to be influential in increasing the seriousness of the accident in all sections. Environmental factors, road conditions, and accident factors were identified as the main influential factors in the tunnel access zone. In contrast, accident and tunnel factors in the tunnel inner zone were found to be the influencing factors. In particular, it was found that serious accidents (A, B) occurred in all sections when a rollover accident occurred. CONCLUSIONS : This study confirmed that the influencing factors and the probability of accident occurrence differed between the tunnel access zone and inner zone. Most importantly, when the vehicle was overturned after the accident occurred, the results of the influencing factors were different. Therefore, the results can be used as a reference for establishing safety management strategies for tunnels or underground roads.

This paper analyzed a survey of 388 general target samples to analyze the correlation between disaster safety costs and human risk factor analysis and evacuation behavior due to tunnel accidents. Considering the impact of the tunnel accident on disaster safety costs and the correlation between human evacuation and risk factors in the tunnel environment, the system should be reorganized to reflect the tunnel’s basic plan, tunnel cross-section, tunnel installation.

2011년∼2016년 고속도로 교통사고 정보 자료에 따르면 고속도로에서는 매년 9,200건 이상의 교통사고가 발생하고 있는 것으로 나타났다. 이 중 봉평터널 버스 6중 추돌사고(2016년), 둔내터널 부근 버스 추돌사고(2017년)와 같은 중차량으로 인한 대형 교통사고는 사회적으로 큰 반향을 불러일으키고 있다. 이에 본 연구에서는 고속도로 교통사고 정보 자료를 이용하여 사고등급, 사고원인, 사고유형, 사고차량수 등 다양한 측면에서 터널부 교통사고에 대한 현황 분석을 수행하였다. 고속도로 터널 연장에 따른 교통사고 현황을 분석하기 위하여 터널 연장 1km를 기준으로 1km 미만 터널, 1km 이상으로 구분하여 분석을 수행하였다. 고속도로 전체 터널 중 터널 내에서 교통사고가 발생한 터널을 구분해 보면 ‘1km 이상’터널은 160개소 ‘1km 미만’ 터널은 369개소로 나타났다. 교통사고 발생 터널의 평균연장은 고속도로 전체 터널의 평균연장에 비해서 긴 것으로 나타났다. 고속도로 터널 연장에 따른 교통사고 현황은 ‘1km 미만’ 터널의 사고 건수가 ‘1km 이상’ 터널에 비해서 많은 것으로 나타났다. 그러나 A급 교통사고 건수, 사망자 수, 부상자 수의 경우 ‘1km 이상’ 터널이 더 많은 것으로 분석되었다. 교통사고가 발생한 터널의 평균 교통사고 건수, 평균 사망자 수 평균 부상자수는 ‘1km 이상’ 터널이 ‘1km 미만’ 터널에 비해서 많았으며 교통사고 당 평균 사망자 수 및 평균 부상자 수 또한 많은 것으로 나타났다. 고속도로 노선별 터널부 교통사고 건수는 ‘순천완주선’이 총 278건으로 터널부 교통사고가 가장 많이 발생한 노선으로 나타났으며, 터널부 B급 이상 교통사고 건수의 경우 ‘중부내륙선’이 22건으로 타 노선에 비해서 심각한 교통사고의 발생 빈도가 월등히 높은 것으로 파악되었다. 고속도로 일반부와 터널부 교통사고 분석결과 일반부에 비해서 터널부의 A∼C급 사고 비율이 높은 것으로 나타났다. 사고원인 중 운전자 요인 비교결과 일반부는 ‘과속’이 가장 높은 비율을 차지한 반면에 터널부는 ‘주시태만’과 ‘졸음’이 높은 비율을 차지하는 것으로 나타났다. 사고차량 수별 교통사고 비율은 일반부의 경우 차량 ‘1대’의 단독 사고 비율이 74.1%, ‘2대’가 18.7%인 반면에 터널부는 일반부에 비해서 ‘2대’인 경우가 6.8%p 높은 것으로 나타났다. 고속도로 터널부 교통사고 중 사고원인차가 화물차, 승합차, 트레일러, 특수차량 등 중차량에 해당하는 교통사고 자료 분석결과 터널부 교통사고 중 B급 이상 사고 비율은 3.5%인 반면에 중차량 교통사고의 비율은 5.6%로 중차량으로 인한 사고의 피해 정도가 더 큰 것으로 나타났다. 사고원인의 경우 일반부 교통사고 및 터널부 일반 교통사고와 달리 터널부 중차량 교통사고의 경우 ‘차량요인’에 의한 교통사고가 ‘기타요인’에 비해서 높은 비율을 차지하는 것으로 나타났다. 사고 차량수는 터널부 일반 교통사고에 비해서 사고차량 수 ‘1대’의 비율은 3.2%p 감소한 반면 ‘2대’의 비율은 1.9%p 상승한 것으로 나타났다. 고속도로 터널부 중차량 교통사고의 연평균 치사율은 5.72%로 터널부 일반 교통사고에 비해서 2.65%p 높은 것으로 나타났으며 사고건당 부상자수 또한 연평균 0.1명 높게 나타났다

Namsan road are taxis in the engine room fires (07/14/2011 18:05) in the tunnel, and the driver of the vehicle was 100 passenger car and more than 500 evacuated were disasters. Pole road vehicles within the tunnel if there is a fire tunnel fire occurred at a two-way evacuation difficult and rapid evacuation is difficult and mass casualties are concerned, the number of casualties is feared. In this study, by considering the problems and improve the Namsan 1,2,3 Tunnel In case of fire, the best disaster response is to come up with ways.

과천터널은 서울지하철 4호선 연장구간으로서 사당에서 금정역까지를 말한다. 이러한 장대터널 전 구간에 대해서 새로운 터널유지관리시스템을 적용하기에는 한계가 있어 약 40m 구간의 박스터널 구간을 선정하여 새로운 터널유지관리시스템을 적용하였다.