한국도로공사에서는 전 세계적인 기후위기 대응에 동참하고, 탄소중립기본법, 탄소중립 녹색성장 기본계획 등 정부의 탄소중립 정책 에 부응하기 위하여 “생애전주기 친환경 대응체계”를 구축하였으며, 이에 도로포장의 생애주기 동안 발생되는 탄소배출량을 산출하기 위한 생애전주기평가(Life Cycle Assessment, LCA)의 필요성이 점차 대두되고 있다. 한국도로공사에서는 매년 고속도로 포장상태 모니터링 데이터를 활용하여 공용성을 예측함으로써 포장 유지관리 전략에 활용하고 있으나 이는 거시적인 측면에서의 포장 공용성 모델로 고속도로 포장의 형식, 재료, 공법 등을 고려한 미시적 측면에서의 공용성 모델 개발 및 개발 절차 정립이 필요할 것으로 판단된다. 따라서, 본 연구에서는 고속도로 장기공용성 관측구간(Long Term Pavement Performance, LTPP) 데이터베이스(DB)를 활용하여 고속도로 JCP 공용성 모델을 개발하기 위한 기초연구를 수행하였다. 본 연구에서는 포장상태지수(Highway Pavement Condition Index, HPCI), 표면손상(Surface Distress, SD), 종단평탄성(International Roughness Index, IRI)를 종속변수로, 각 구간별 누적 교통 및 기후인자를 독립변수로 설정하여 다양한 교통 및 환경 영향인자에 따 른 고속도로 JCP 공용성을 예측하기 위하여 기술통계분석, 상관분석, 분산분석, 다중회귀분석을 수행하였다. 고속도로 JCP 공용성에 대한 다중회귀분석 결과, HPCI 모델의 수정된 R2이 0.614.로 SD 모델(0.413)이나 IRI 모델(0.317)에 비하여 높은 설명력을 보이는 것으로 나타났으며, 개별 모델의 회귀식은 통계적으로 유의한 것으로 나타났다.

고속도로는 콘크리트 포장을 사용하는 경우 장수명 포장을 적용하여 공용수명을 증진시키고 차단을 최소화 하여 사용자 편의성을 높이는 방향으로 패러다임이 변화하고 있다. 이때 연속철근 콘크리트 포장(이하:CRCP)는 세계적으로 검증된 장수명 포장으로 국내는 일반 토공구간에 사용하고 터널의 경우 철근으로 인한 공사차량 진입로가 확보되지 않아 JCP를 사용하고 있는 실정이다. 터널 내부는 눈비가 오는 경우에도 포장에 직접 접하지 않아 제설제를 뿌릴 필요가 없어 철근 부식의 우려가 적고 하부 지지력이 크며 온도변화가 작아 토공구간에 적용할 때 보다 공용수명이 늘어나는 장점이 있다. 터널에 CRCP를 적용하는 경우 일반구간과 다른 설계를 적용해야 하며 시험시공을 수행하기 위한 국내외 사례조사를 실시하여 적용 방향 수립에 참고하였다. 국내는 JCP 설계 지침을 통해 포장 두께 및 타이바 설치방법을 제시하나 국내 CRCP 특성을 고려하고 있지 못하고 있는 상태로 일본의 경우 일반 구간 보다 얇은 두께를 적용하며 동일한 철근비를 적용해 철근비 감소에 따라 터널 입출구에서 발생할 수 있는 배근 전이구간 발생, 열화 발생에 장점을 가지는 것으로 조사되었다. 또한, 아스콘 포장과 접하는 경우 전이슬래브를 설치하여 연결하는 것이 조사되었고 미국에서도 전이 슬래브를 통해 단부에서 발생하는 수축/팽창을 흡수하고 아스콘 포장과 접속부 역할을 할 수 있도록 하는 것이 조사되었다. 국내외 사례와 국내 CRCP의 현재 설계기준은 시험시공을 위한 설계방향 설정에 사용하는 것이 합리적으로 판단되었다. 시험시공 구간 철근비는 토공구간 기준 철근비(0.68%)와 최소 철근비(0.60%)를 적용해 계측을 통해 국내에 적합한 철근비를 도출하되 시공구간 전후에서 아스콘 포장과 연결되므로 전이슬래브를 도입/검토하여 국내에 적합한 설계를 도출하는 것이 필요한 것으로 사료되었다.

도시의 확장 및 광역화로 지상에서의 물리적인 도로 공급 및 확대는 현실적으로 어려운 상황에 직면하였으며, 이를 해결하기 위한 정책의 일환으로 경부고속도로 지하화 사업으로 대표되는 고속도로 지하화 사업이 추진되고 있다. 지하공간을 이용한 도로의 입체적 확장은 새로운 도로 공급용지의 공간적 확대뿐 아니라 지상도로의 교통량 분산으로 교통정체 완화, 차량으로 인한 소음 및 대기오염 문제 완화 등 도로교통체계의 효율성 및 문제점을 개선할 것으로 판단된다. 그러나 현재까지는 지하도로의 설계 및 시공 관련 기술을 위주로 개발 및 적용되고 있어, 운영 및 안전관리에 필수적인 지하고속도로 교통류 관리에 관한 연구는 이론적 수준에 머물고 있는 한계가 상존한 상황에 있다. 이에 본 연구는 지하고속도로 안전 향상을 위한 사고 예방 및 대응 기술 개발의 전단계로 유고 상황에 대응하기 위한 교통관리 개념을 유고 상황에 따라 변화되는 혼잡 지속시간을 추정할 수 있는 교통류 진단과 지하고속도로 내 유고 발 생 후 교통류 혼잡 회복 및 상태 안전화로 나누어 제안하였다. 이를 기반으로 향후 추진될 기술 개발의 단계를 교통류 변동 지표 개 발, 교통류 진단 알고리즘 개발, 교통류 해석ㆍ추정 알고리즘 개발, 교통관리 현장 적용 및 검증의 4단계로 기술 개발 로드맵을 제시 하였다. 본 연구의 결과는 향후 추진되는 K-지하고속도로 안전 확보를 위한 사고 예방 및 대응 기술 개발에 대한 실효성 및 신뢰성을 높이는데 기여할 것으로 사료된다.

국토교통부는 고속도로 접근성 개선을 통한 지역균형 발전을 위해 남북측과 함께 동서축으로 지속적인 신설 사업을 계획하고 있다. 이에 따라 고속도로 노선의 관리 연장이 증가하고 대부분 산지인 우리나라 지형 특성에 의해 터널 구간도 증가하고 있다. 터널 구간 포장의 경우 환경 조건 등의 영향으로 전이구간에서 파손이 다수 발생하고 있다. 따라서 본 연구에서는 장대터널 구간에서 조사된 PMS 데이터를 분석하여 터널 진입 전 후 PMS 조사 인자별 변화를 분석하였다. 분석 조건은 1) 1km 이상의 장대터널 포장상태조사 자료 분석, 2) SD(Surface Distress), IRI(International Roughness Index), HPCI(Highway Pavement Condition Index) 인자 분석, 3) SD 상세 데이터(균열, 패칭, 스폴링 등) 분석이다. 이를 활용하여 터널 진입 전·후 포장 연장 변화에 대한 분석인자별 변화 검토, 터널 진입 전· 후 분석인자별 평균값 변화 비교, 터널 내 포장의 선형 균열, 패칭, 스폴링 파손 상세 검토를 수행하였다. 분석 결과 터널 진입 후 30~40m 까지 변화가 크게 나타나는 것을 확인하였으며, 평균값 비교 결과 SD 값이 진입 전 후 약 66% 차이가 나타난다. SD 상세데 이터 분석 결과는 균열 및 스폴링 파손 등에 대해 100m 구간 내에 약 3.35m2 정도 패칭보수가 이루어졌다. 장대터널의 경우 터널 입 구와 터널 내부의 환경 조건이 상이하여 전이구간에서 터널 내부보다 파손이 다수 나타나는 것을 확인하였다.

PURPOSES : This study aims to calculate the estimation of travel time saving benefits from smart expressway construction by considering the willingness to pay for automated vehicles. METHODS : In this study, data were collected from 809 individual drivers through a stated preference survey. A multinomial logit model was constructed to analyze the choice behavior between arterial roads, expressways, and smart expressways. Through this, the values of time and benefits were estimated. RESULTS : The value of time was calculated at 19,379 won per vehicle per hour for arterial roads and expressways and 23,061 won per vehicle per hour for smart expressways. Applying these values to the Jungbu Naeryuk expressway, we evaluated the demand change and benefits resulting from the improvement to the smart expressways. The results show that the traffic volume on the Jungbu Naeryuk expressway is expected to increase by 4.7% to 20.7% depending on the changes in capacity. CONCLUSIONS : The travel time saving benefits are estimated as positive, resulting from the construction of smart expressways. The benefits resulting from the construction of new smart expressways are expected to be enhanced due to the anticipation of more significant time-saving effects.

PURPOSES : This study aims to provide societal benefits that demonstrate the effectiveness of remodeling projects, thereby providing a basis for activating and systematically and continuously promoting remodeling projects METHODS : Using the International Roughness Index (IRI) and World Bank's HDM-4, a model for vehicle operating costs was estimated. The change in vehicle operating costs was calculated by inputting the pre- and post-remodeling IRI values into the estimated model. Additionally, the future IRI over the life cycle was derived using the results of a study on the changes in pavement conditions between conventional and remodeling methods. The vehicle operating costs for different maintenance alternatives were compared by inputting them into the estimated model. RESULTS : The improvement in road smoothness after the project resulted in an annual vehicle operating cost benefit of approximately 1.6 billion won, with an estimated benefit per kilometer of approximately 64 million won. Furthermore, a comparison of vehicle operating costs for maintenance alternatives over the life cycle revealed that the remodeling method led to savings of 2.1 billion won compared with conventional methods. CONCLUSIONS : The findings of this study will serve as fundamental data supporting the necessity and justification for remodeling projects, particularly in the current scenario, where the need for maintenance of existing roads exhibits a faster growth trend than the extension of new roads. Additionally, this study could be supplemented by further research focusing on the consideration of pavement conditions in unit cost estimation and additional benefit estimation studies tailored to remodeling projects.

PURPOSES : This study is to initiated to estimate the impact of mixed traffic flow on expressway section according to the market penetration rate(MPR) of automated vehicles(AVs) using a enhanced intelligent driver model(EIDM). METHODS : To this end, microscopic traffic simulation and EIDM were used to implement mixed traffic flow on basic expressway section and simulation network was calibrated to understand the change of impact in mixed traffic flow due to the MPR of AVs. Additionally, MOEs of mobility aspects such as average speed and travel time were extracted and analyzed. RESULTS : The result of the impact of mobility MOEs by MPR and level of service indicated that 100% MPR of AVs normally affect positive impact on expressway at all level of service. However, it was analyzed that improvements in the level of service from LOS A to C are minimal until the MPR of AVs reaches 75% or higher. CONCLUSIONS : This research shows that impact of MPR of AVs using EIDM of mixed traffic flow on basic expressway. Increasing MPR of AVs affects positive impact on expressway at all level of services. However, MPR from 25% to 75% of AVs in LOS A to C shows minimal impacts. Therefore, to maximize the effectiveness of AVs, appropriate traffic operation and management strategies are necessary.

PURPOSES : This study is to evaluate environmental improvement effects of underground road project, as a case study of ‘Seobu’underground expressway project in Korea. METHODS : The environmental improvement effects of underground road construction were classified into tree sector in this study – air quality, noise, and thermal environment. To evaluate these effects, this study collected and divided environment dataset into before, during, and after ‘Seobu’underground expressway construction, and compared the change of values with entire city. In addition, the quantification method of environmental improvement effects was suggested based on the literature review. RESULTS : The result of this study indicates that there exist significant improvement effects of urban environment after the construction of ‘Seobu’underground expressway. Specifically, the concentration of particulate matters (PM10) and daytime/nighttime noise, and land surface temperature (LST) were improved along the expressway. In addition, the overall environmental benefit of ‘Seobu’ underground expressway was estimated to 1.15 billion won per year. CONCLUSIONS : To promote systematic and consistent underground road project, it is required to establish legislative system for evalauting and supporting urban improvement effects.

PURPOSES : This study aims to perform a quantitative analysis of Forward Collision Warning and crash frequency using heavy vehicle driving data collected in expressway driving environments, and to classify the driving environments where Forward Collision Warnings of heavy vehicles occur for accident-prone areas and analyze their occurrence characteristics. METHODS : A bivariate Gaussian mixture model based on inter-vehicle distance gap and speed-acceleration parameters is used to classify the environment in which Forward Collision Warning occurs for heavy vehicles driving on expressways. For this analysis, Probe Vehicle Data of 80 large trucks collected by C-ITS devices of Korea Expressway Corporation from May to June 2022. Combined with accident information from the past five years, a detailed analysis of the classified driving environments is conducted. RESULTS : The results of the clustering analysis categorizes Forward Collision Warning environments into three groups: Group I (highdensity, high-speed), Group II (high-density, low-speed), and Group III (low-density, high-speed). It reveals a positive correlation between Forward Collision Warning frequency and accident rates at these points, with Group I prevailing. Road characteristics at sites with different accident incidences showed that on-ramps and toll gates had high occurrences of both accidents and warnings. Furthermore, acceleration deviation at high-accident sites was significant across all groups, with variable speed deviations noted for each warning group. CONCLUSIONS : The Forward Collision Warning of heavy vehicles on expressways is classified into three types depending on the driving environment, and the results of these environmental classifications can be used as a basis for building a road environment that reduces the risk of crashes for heavy vehicles.

PURPOSES : This study proposes a framework for promoting future expressway remodeling projects by reviewing similar overseas cases and comparing them with current Korean expressway remodeling projects. METHODS : Based on a literature review, this study examines the major issues in expressway remodeling projects and proposes the development of a framework for establishing and promoting such projects. This framework provides detailed guidance by categorizing the project into legal system adjustments, traffic management plans, and social consensus. RESULTS : The diagnosis of issues in domestic expressway remodeling projects revealed significant problems in conceptual aspects, criteria for project evaluation, formulation of traffic diversion strategies, and deficiencies in related legal frameworks. To address these issues, a framework for advancing future remodeling projects was established based on the results of overseas case studies. CONCLUSIONS : As roads deteriorate, the demand for remodeling projects to restore them increases. However, the current implementation of remodeling projects lacks systematic procedures. This study serves as foundational research for establishing an environment conducive to the smooth progress of such projects. By initiating subsequent research, conditions for the smooth progress of remodeling projects are expected to be established.

PURPOSES : In this study, a model was developed to estimate the concentrations of particulate matter (PM2.5 and PM10) in expressway tunnel sections. METHODS : A statistical model was constructed by collecting data on particulate matter (PM2.5 and PM10), weather, environment, and traffic volume in the tunnel section. The model was developed after accurately analyzing the factors influencing the PM concentration. RESULTS : A machine learning-based PM concentration estimation model was developed. Three models, namely linear regression, convolutional neural network, and random forest models, were compared, and the random forest model was proposed as the best model. CONCLUSIONS : The evaluation revealed that the random forest model displayed the least error in the concentration estimation model for (PM2.5 and PM10) in all tunnel section cases. In addition, a practical application plan for the model developed in this study is proposed.

PURPOSES : The primary objective of this study is to analyze the relationship between the factors that affect traffic incident duration in the mainline, tunnel, and ramp segments of an expressway. In addition, this study derived the most suitable statistical prediction model based on various incident duration distributions. METHODS : South Korean expressway crash data for 11 years, from 2011 to 2021, were analyzed. The incident durations on the mainline, tunnel, and ramp segments were selected using the accelerated failure time model, which is a parametric survival analysis approach. RESULTS : The mainline segment showed that the incident duration increased during accidents, including guard pipe collisions, multivehicle collisions, and snowfall. In particular, collisions in a tunnel with shoulder facilities increase the incident duration, while decreasing the time in the ramp segment. CONCLUSIONS : The incident duration model for each segment type yielded the most accurate results when applying a log-logistic distribution.

PURPOSES : The primary purpose of this study is to establish a crash probability model based on a statistical method that explains the relationship between regressor and explanatory variables using both fixed and random effects to control the heterogeneous characteristics of the observed data. In addition, an attempt was made to discover the leading cause of crashes by vehicle type, including passenger car, bus, truck, and trailer. METHODS : The levels of each route and day of the week are grouped using raw expressway crash data for 10 years from 2012 to 2021, and a multilevel mixed-effect logit model is constructed for each vehicle type assuming that the error terms are derived from the hierarchical structure of the group to which they belong. RESULTS : Speeding and obstacles on the road are significant factors that increase the probability of passenger car crashes, and bus crashes have a high rate at toll gates on weekdays. CONCLUSIONS : The multilevel mixed-effect logit model derived in the study has higher accuracy than the general logit model, confirming that mixed-effect analysis is plausible.