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.