Korea Expressway Research Articles

Laboratory Evaluation of Wear Particle Emissions and Suspended Dust in Tire–Asphalt Concrete Pavement Friction

This study aims to evaluate the tire–road-wear particles (TRWPs) and suspended dust generated based on the nominal maximum aggregate size (NMAS) of the polymer-modified stone mastic asphalt (SMA) mixtures indoors. The SMA mixtures containing styrene butadiene styrene (SBS) polymer and the NMASs of 19, 13, 10, 8, and 6 mm were used. Dust was generated from the wear of the tires and the pavement inside the indoor chamber by using the laboratory tire–road-wear particle generation and evaluation tester (LTRWP tester) developed by Korea Expressway Corporation (KEC). In this method, a cylindrical asphalt-mixture specimen rotates in the center, and a load is applied using three tires on the sides of the test specimen. During the test, a digital sensor was used to measure the concentration for each particle size. After the test was completed, the dust was collected and weighed. According to the test results, the generated TRWP emissions were reduced by approximately 0.15 g as the NMAS of the SMA mixture decreased by 1 mm. TRWP emissions decreased by 20% when using the 6 mm SMA mixture compared to the 13 mm SMA mixture. For practical application, a predicted equation of TRWP emissions estimation was developed by using the concentration of suspended dust measured by the digital sensor in the LTRWP tester. LTRWP can be used as an indoor test method to evaluate pavement and tire materials to reduce the amount of dust generated from tire and pavement wear.

A Study on Innovative Design Approaches for Implementing an Intelligent ICT-Based Smart Highway

This research, conducted over a three-year period starting from 2020, was a collaborative project between practitioners in the field of VE design and the Korea Expressway Corporation, aimed at innovating the design VE project to construct an intelligent ICT-based smart highway and enhancing highway driving performance and customer satisfaction.
 The research included R&D support for payment and management systems integrated with IOT technology, the application of the developed prototype at highway sites, and analysis of user performance evaluation. Based on the Innovation Work Roadmap of the Korea Expressway Corporation, the research process involved collaboration between a public participation group and an expert group, considering the technical feasibility of data-based ICT technology through the National Idea VE Contest.
 The final VE design results were implemented at the Seongnam tollgate site with budget support from relevant departments, followed by a satisfaction survey. It is expected that the continuous contributions to achieving an ESG society, such as the increase in the number of customers using the tolling zone equipped with smart upgrades, along with their satisfaction rate, and the reduction in carbon emissions and total settlement time of highway users, will be sustained.

Mitigating air and noise pollution through highway capping: The Bundang-Suseo Highway Cap Project case study

Highways, while vital for transportation, often lead to heightened air and noise pollution, adversely affecting nearby communities. This study delves into the effectiveness of highway capping, a sustainable urban development strategy, in addressing these environmental challenges, with a specific focus on the Bundang-Suseo Highway in South Korea. This study employed a multifaceted approach, incorporating on-road monitoring, in situ measurements, and vertical assessments using UAVs. Following the cap's installation, the area experienced more stable pollutant levels, marking a notable shift from the previously fluctuating conditions heavily influenced by the highway. In-depth in situ monitoring near the cap revealed significant reductions in noise and pollutants like UFP and BC. Furthermore, UAV monitoring captured these changes in pollutant levels at different altitudes. Notably, the installation of the highway cap led to increased PM2.5, PM10, and NO2 levels at ground level, but a decrease above the cap, emphasizing the critical importance of intentional highway cap design in enhancing urban air quality and reducing exposure to harmful pollutants. This research yields invaluable insights for urban planners, health authorities, and policymakers, aiding the precise identification of pollution-prone areas and advocating for improved highway cap design to enhance urban environments.

Bridge Frost Prediction Using K-nearest Neighbor Classifier

Background: Considering the frequent occurrence of accidents on icy bridges during winter nights, it would be advantageous to notify both road managers and drivers regarding the most perilous areas. This notification would allow road managers to address the icy conditions by applying de-icing substances, while drivers could be more adequately prepared for potential hazards. Methods: In this study, the focus was on investigating k-nearest neighbor algorithms to predict nighttime icing caused by frost on three distinct bridges located on the National Highways in Korea. The algorithms utilized atmospheric data as input, which was obtained from the weather agency's website through an open API. The input data included relative humidity, air temperature, and dew point temperature, as well as the disparities in air temperature and humidity between two consecutive days. Results: In order to assess the effectiveness of the prediction models, reference data were created using the fundamental principle that ice is formed when the temperature of the pavement is below freezing and lower than the dew point temperature. Consequently, the developed algorithm demonstrated favorable performance, achieving an accuracy of 95% when evaluated using a test dataset that occupies 30% of the entire data. Conclusion: Considering the increasing focus on preventive maintenance, these newly developed forecasting models can be employed proactively as a preventive measure against icing. This proactive approach will ultimately contribute to improving traffic safety on winter roads.

Exploratory Field and Laboratory Investigation on the Use of Noncontact Digital Ski Sensor in the South Korea Expressway Network

In the case of asphalt pavement construction, better smoothing and reliable material performance acquisition are essential. In South Korea, the next-generation asphalt pavement-smoothing technology, known as the noncontact digital ski (NCDS), started to be used in expressway construction in 2018, making this system an essential tool in the paving industry. The present work thoroughly assessed how employing the NCDS system affected the response of the pavement material at low temperatures. Portions of paved roads with and without NCDS were assessed for the international roughness index (IRI, m/km). The development of thermal stress propagation was then examined using the bending beam rheometer on asphalt samples from the road. Based on straightforward visual and statistical analysis, it was discovered that using NCDS produces significantly lower IRI and reduced thermal stress, which raises the possibility that using NCDS has the potential for better low-temperatures predictions.

RMIc-3.0 Program Development to Prioritize Concrete Pavement Sections for Large-scale Repair Works

Large-scale repair works (LSRW) are expensive and time-consuming, and therefore cannot be carried out simultaneously for all deteriorated pavements; hence, they are performed based on urgency. In Korea, the re-modeling index (RMI) program versions 1.0 and 2.0 were developed to predict the urgency of the LSRW on expressway concrete pavements. In this study, version 3.0 of the RMI program was developed to address the drawbacks found in version 2.0 of the program. The model used in the program was improved by using the equivalent single-axle load instead of the annual average daily traffic used in the previous version, to consider the damage to pavement caused by heavy vehicles. In addition, another model was modified by combining the winter climate conditions with the annual deicing salt usage, which was used as the only variable considering the environmental factors in the previous version. The international roughness index and surface distress prediction models, which were not separated by pavement type in version 2.0 of the program, were separated into jointed concrete pavement and continuously reinforced concrete pavement. The logic for predicting future RMI was also reasonably improved. In addition, the logic of categorizing the entire expressway concrete pavement section into homogeneous sections was objectively improved for more effective LSRW. Consequently, for 2023, the Korea Expressway Corporation selected for LSRW those homogeneous sections that were evaluated as urgent by the RMI3.0 program.

Identification of Emerging Roadkill Hotspots on Korean Expressways Using Space-Time Cubes.

Collisions with wild animals on high-speed expressways not only lead to roadkill but can also cause accidents that incur considerable human and economic costs. Based on roadkill data from 2004-2019 for four common wildlife species involved in collisions with vehicles on expressways in Korea (water deer, common raccoon dog, Korean hare, and wild boar), the present study conducted optimized hotspot analysis and identified spatiotemporal patterns using a space-time cube (STC) approach. Temporal and spatial differences in the roadkill data were observed between species. Water deer were the most common roadkill species of the four studied, with hotspots in the southern region of the capital area, in the Chungnam region, and in the western Chungbuk and Gangwon-do regions. However, the instances of water deer roadkill over time differed between each region. In addition, it was found that the number of cases of wild boar roadkill has increased recently. In particular, a number of new hotspot areas were observed centered on the metropolitan area Gyeonggi-do, which contains a high population and significant infrastructure. Overall, the emerging hotspot analysis based on STCs was able to determine cold spot and hotspot trends over time, allowing for a more intuitive understanding of spatiotemporal clustering patterns and associated changes than cumulative density-oriented hotspot analysis. As a result, it becomes easier to analyze the causes of roadkill and to establish reduction measures according to priority.

Artificial Neural Network Modeling on PM10, PM2.5, and NO2 Concentrations between Two Megacities without a Lockdown in Korea, for the COVID-19 Pandemic Period of 2020

The mutual relationship among daily averaged PM10, PM2.5, and NO2 concentrations in two megacities (Seoul and Busan) connected by the busiest highway in Korea was investigated using an artificial neural network model (ANN)-sigmoid function, for a novel coronavirus (COVID-19) pandemic period from 1 January to 31 December 2020. Daily and weekly mean concentrations of NO2 in 2020 under neither locked down cities, nor limitation of the activities of vehicles and people by the Korean Government have decreased by about 15%, and 12% in Seoul, and Busan cities, than the ones in 2019, respectively. PM 10 (PM2.5) concentration has also decreased by 15% (10%), and 12% (10%) in Seoul, and Busan, with a similar decline of NO2, causing an improvement in air quality in each city. Multilayer perception (MLP), which has a back-propagation training algorithm for a feed-forward artificial neural network technique with a sigmoid activation function was adopted to predict daily averaged PM10, PM2.5, and NO2 concentrations in two cities with their interplay. Root mean square error (RMSE) with the coefficient of determination (R2) evaluates the performance of the model between the predicted and measured values of daily mean PM10, PM2.5, and NO2, in Seoul were 2.251 with 0.882 (1.909 with 0.896; 1.913 with 0.892), 0.717 with 0.925 (0.955 with 0.930; 0.955 with 0.922), and 3.502 with 0.729 (2.808 with 0.746; 3.481 with 0.734), in 2 (5; 7) nodes in a single hidden layer. Similarly, they in Busan were 2.155 with 0.853 (1.519 with 0.896; 1.649 with 0.869), 0.692 with 0.914 (0.891 with 0.910; 1.211 with 0.883), and 2.747 with 0.667 (2.277 with 0.669; 2.137 with 0.689), respectively. The closeness of the predicted values to the observed ones shows a very high Pearson r correlation coefficient of over 0.932, except for 0.818 of NO2 in Busan. Modeling performance using IBM SPSS-v27 software on daily averaged PM10, PM2.5, and NO2 concentrations in each city were compared by scatter plots and their daily distributions between predicted and observed values.

ESG-oriented Governance Work System for Smart Highway Implementation

This study was promoted to prepare an ESG-oriented work system for Korea Expressway Corporation through sustainable highway construction, IOT-based smart highway preparation, and establishment of a broad convergence business governance system between multiple ministries and implementing entities. Based on the 2nd Basic Plan for Landscape Policy (2020~2024) and the Public Design Promotion Act (2018~2022), the study was conducted through the improvement of the highway design method to be applied for four years from 2021 to 2024, the changes in construction and social conditions related to expressways, the analysis of policies and plans to secure consistency with the 'Korean New Deal', and the analysis of the project performance and work promotion system that the Korea Expressway Corporation's business execution organization has promoted together with each government department. The results of this research are expected to help the Korea Expressway Corporation establish the 21st Innovation Plan for the phased construction of a “100-years landscape with people” and the preparation of a sustainable future highway environment creation project for the lives and safety of the people.

Development of Risk-Situation Scenario for Autonomous Vehicles on Expressway Using Topic Modeling

Growing interest has recently been paid to the development of autonomous vehicle scenarios, and corresponding research is being conducted on various methodologies and on the generation of scenarios including technological elements. However, most studies have focused on frequently-occurring accident types or representative accident situations; thus, there is a lack of studies on scenarios considering unpredictable accidents. Proper preparation is required for accident situations because even a small traffic accident that is less likely to occur can lead to fatalities if it is difficult to predict. Accordingly, this study established accident situations based on the Pegasus layer model by using unstructured text data to explain traffic accidents on expressways in Korea. The established accident situations were classified into three types (Typical Traffic/Critical Traffic/Edge Case) according to frequency. Topic modeling was applied to the Edge Case class, i.e., the least likely to occur and thus difficult to predict, to analyze the characteristics of groups and develop risk-situation scenarios for autonomous vehicles based on actual accident data.

Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models

Despite the not-a-long history of public-private partnerships (PPPs) in South Korea for about 20 years, they play a significant role and share in the highway sector. Road safety is one of the most critical public values in the construction and operation of highways. However, the safety achievement of the PPP projects has not been paid enough attention to and comprehensive and objective evaluation efforts were insufficient. This study investigates the evidence of whether the PPP highways in Korea have experienced a higher degree of road safety compared to the public highways through an empirical analysis. To this end, several crash-frequency prediction models were estimated for all toll highways in the country, including 18 PPP highways opened between 2000 and 2018. The numbers of accidents and casualties, annual traffic volume, and other roadway or PPP-project characteristic data for the five years were collected and organized as unbalanced panel datasets. To account for the unobserved heterogeneity and temporal correlation among the analysis units, i.e., highway segments, panel data models were estimated and compared with cross-sectional models. The modeling results showed that the positive effect of PPPs on road safety in terms of the number of accidents and casualties for the toll highways in Korea exists. The findings of this study offer important policy implications for countries that are pursuing to extend the partnerships with private sectors by helping policymakers to refine or improve the existing PPP policies.

Incident Duration Time Prediction Using Supervised Topic Modeling Method

Accurate prediction of the duration of traffic incidents is one of the most prominent prerequisites for effective implementation of proactive traffic incident management strategies. This paper presents a novel method for immediate prediction of traffic incident duration using an emerging supervised topic modeling. The proposed method employs natural language processing techniques for semantic text analysis of the text-based incident traffic incident dataset. The model applies the labeled latent Dirichlet allocation approach, and it is trained using 1,466 incident records collected by the Korea Expressway Corporation from 2016 to 2019. For training purposes, the proposed method divides the incidents into two groups based on the incident duration: incidents shorter than 2 h and incidents lasting 2 h or longer, following the incident management guidelines of the Federal Highway Administration Manual on Uniform Traffic Control Devices for Streets and Highways (2009). The model is tested with randomly selected incident records that were not used for the model training. The results demonstrate overall prediction accuracies of approximately 74% for incidents lasting up to 2 h, and 82% for incidents lasting 2 h or longer.

Determination of Partial Depth Repair Size for Spalling of Jointed Concrete Pavements Using the Impact Echo Method

When spalling occurs at a concrete pavement joint, partial depth repair (PDR) is implemented by removing the damaged part of a slab and filling the space with repair materials. However, re-repair is frequently also required because additional distress develops at the boundary of the repaired area due to improper PDR size in addition to poor quality of materials and construction methods. For the sustainability of pavement structures, it is necessary to study the PDR size based on the mechanical theory. Therefore, in this study, the PDR size for spalling was suggested based on the results of laboratory and field tests conducted using the impact echo (IE) method. The dynamic modulus estimated in the laboratory using the IE and forced resonance methods were compared for concrete specimens subjected to repetitive freeze–thaw cycles. In addition, the correlations of the dynamic modulus estimated by the methods with the compressive strength and absorption coefficient were analyzed. As a result, the IE method, for which vibration could be estimated on the same side of the specimen where impaction was applied, was selected for use on the pavement surface. Furthermore, the short-time Fourier transform technique was used instead of the fast Fourier transform, which has been commonly used for nondestructive methods, to minimize the noise in the field and, consequently, to estimate the dynamic modulus more accurately. The dynamic modulus was estimated according to the distance from the spalling end using the IE method at the Korea Expressway Corporation test road to identify the damaged range in the slab based on the severity of spalling. The dynamic modulus, compressive strength, and absorption coefficient tests were conducted in the laboratory for specimens cored from the concrete slab where the field test was performed. Finally, the PDR size was suggested according to the severity of spalling based on the damaged range in the slab, as determined by the field test and laboratory test results.

로지스틱회귀모형을 이용한 위험물수송차량 교통사고확률 분석 연구

Hazardous materials transport vehicle crashes on highways occur steadily with an average of 30 cases per year, and leakage of Hazardous materials due to traffic accident causes enormous socioeconomic losses. Studies related to truck safety have been conducted for a long time in Korea, but studies on traffic accidents and influencing factors of hazardous materials transport vehicles have not received attention from researchers. Therefore, this study aims to predict the cause of hazardous materials transport vehicle accidents on highways and the probability of accidents. For this purpose, the highway crash dataset from 2007 to 2020 provided to the Korea Expressway Corporation was collected, and we extracted hazardous materials transport vehicle accidents from the dataset. The logistic regression model was applied for predicting crash probability by selecting four types of crashes, such as fatal and injury, human factor, night-time, and ramp section. As a result of this study, fatal and injury crashes of hazardous materials transport vehicles were derived the most from driver

Highway Regional Classification Method Based on Traffic Flow Characteristics for Highway Safety Assessment.

Accurate regional classification of highways is a critical prerequisite to implement a tailored safety assessment. However, there has been inadequate research on objective classification considering traffic flow characteristics for highway safety assessment purposes. We propose an objective and easily applicable classification method that considers the administrative divisions of South Korea. We evaluated the feasibility of this method through various theoretical analysis techniques using the data collected from 536 permanent traffic volume counting stations for the national highways in South Korea in 2019. The ratio of the annual average hourly traffic volume to the annual average daily traffic was used as the explanatory variable. The corresponding results of factor and cluster analyses with this ratio showed a 61% concordance with the urban, suburban, and rural areas classified by the administrative divisions. The results of two-sample goodness-of-fit tests also confirmed that the difference in the three distributions of hourly volume ratios was statistically significant. The results of this study can help enhance highway safety and facilitate the development and application of more appropriate highway safety assessment tools, such as Road Assessment Programs or crash prediction models, for specific regions using the proposed method.

Spatial Characteristics of Wildlife-Vehicle Collisions of Water Deer in Korea Expressway

In recent decades, rapid industrial growth has accelerated the construction of new roads, which has led to the destruction and isolation of wildlife habitats. Newly constructed roads affect wildlife in many ways. In particular, fatal wildlife-vehicle collisions (WVCs) have a direct impact on wildlife. A substantial number of WVCs occur every year on expressways, where vehicle speeds and vehicle traffic are significant. However, our understanding of the relative importance of the factors associated with areas in which large numbers of WVCs occur on the expressway remains poor. Therefore, herein, we analyze the spatial characteristics of WVCs. The effect of spatial distribution on the occurrence of WVCs was analyzed using the types of land cover in the areas where water deer appear (Cheongju, Boeun, and Sangju) and the areas in which WVCs occur along the Cheongju–Sangju Expressway (CSE). We identified the WVC hotspots by using CSE patrol data recorded between January 2008 and December 2019, and we analyzed the corresponding distribution patterns and land cover characteristics. Along the CSE, a total of 1082 WVCs occurred, out of which collisions involving water deer (Hydropotes inermis argyropus) accounted for 91%. Water deer appear frequently in Forested Areas and Agricultural Land, but the WVC distribution in the Hotspots followed a highly clustered pattern, with a higher proportion of WVCs occurring in Used Areas (areas including buildings such as residential facilities, commercial and industrial facilities, and transportation facilities). Used Areas have a smaller cut slope compared to Forested Areas, and Used Areas are open terrains. Therefore, the occurrence of WVCs will be high given that wildlife can easily access the expressway. Based on these results, we can infer that the landscapes near the expressway influence the occurrence of WVCs. To establish an effective policy for reducing WVCs on a road, the WVC characteristics and spatial distribution of the road should be considered together. Further research on the wildlife ecology and land-use status of WVC hotspots is required to mitigate WVCs on expressways and protect human and animal life. Therefore, if the characteristics of WVC hotspots are analyzed considering the characteristics of various ecosystems, an appropriate WVC reduction plan can be established.

Pressure Relief Joint for Preventing Concrete Pavement Blowup

Blowup refers to concrete pavement distress resulting from compressive failure at joints or cracks when excessive concrete expansion occurs, compressive forces are generated, and the horizontal movement of the pavement is constrained. Blowup occurs because of many reasons including heatwaves caused by abnormal climatic conditions, improper installation spacing between expansion joints, pavement expansion due to an alkali-aggregate reaction, concrete pavement aging, and contraction joint failure. In the summer of 2018, the Korean peninsula experienced the worst heatwave ever recorded, and hence, the possibility of blowup increased. Consequently, the Korea Expressway Corporation established a draft policy for installing pressure relief joints (PRJs) to prevent blowup. In this draft, three installation classes were specified for installing PRJs on in-service roads, and the installation priority for each class was set such that the limited budget could be used efficiently. In addition, the draft presented specific guidelines for installing each class of PRJs and suggested PRJ cross sections that could ensure structural stability. However, the draft lacks systematic research on the causes of blowup and the development of countermeasures and does not provide an engineering basis for the suggested technological solutions to prevent blowup. Therefore, this study aimed to reexamine and complement the suitability of the existing PRJ installation standards through field studies, laboratory experiments, and analytical techniques.

Study on the Increase of the Supporting Capacity of a Cement Milk Pile with Expansive Additives

In this study, an engineering characteristic test was conducted on cement milk using expansive additives during the construction of bored piles. Expansive additive mixtures with various mixing ratios were prepared according to the construction standards of the Korea Expressway Corporation. Segregation resistance, compressive strength, frictional resistance stress, scanning electron microscope images, porosity, and economic feasibility were analyzed. It was found that segregation effects due to expansive additive incorporation were insignificant, and it was confirmed that all specimens exceeded 0.5 N/mm2, the compressive strength standard of the Korea Expressway Corporation pile bearing capacity. Given a water–binder ratio of 83% mixed with 10% expansive additives, frictional resistance increased up to ~35%, skin friction force was significantly improved, and a cost-saving effect of up to ~33.24% was achieved.

Analysis of Roadkill on the Korean Expressways from 2004 to 2019.

Expressways in Korea are high-speed traffic roads connecting important cities. Road infrastructure continues to expand to accommodate the increase in traffic volume associated with the growth of industry and tourism. Here, data on 36,863 roadkill events that occurred on expressway routes managed by the Korea Expressway Corporation between 2004 and 2019 were analyzed. Characterizing patterns of roadkill is important for prioritizing roadkill mitigation measures. We identified consistently increasing or decreasing trends using Mann–Kendall statistics and Sen’s slope. Roadkill was most common in Gangwon Province and was concentrated between May and June and between October and December. Water deer (Hydropotes inermis) was the most common road-killed species. The trend analysis revealed a statistically significant decline in Gangwon Province and a statistically significant increase in the Capital Area and Chungnam Province. There was a significant increase in wild boar (Sus scrofa) roadkill in the first and fourth quarters. Mitigation measures are needed for regions and species showing increasing trends, including water deer in the first to third quarters, periods for which no decline in water deer roadkill was noted.

Rockfall Hazard Analysis Based on the Concept of Functional Safety with Application to the Highway Network in South Korea

Numerous rockfall incidents involving infrastructure damage and loss of life have been reported along roads in mountainous terrain. Previous studies have used quantitative risk assessment approaches to identify the level of rockfall risk. However, appropriate quantitative indicators that are able to describe time-varying risk have not yet been developed. This study aims to develop a rockfall risk mitigation method based on reliability concepts, to classify rockfall data, to model the probability of rockfall occurrence, and to estimate the magnitude of risk reduction through mitigation measures. A synthetic measure of rockfall risk is proposed, which allows to compare directly and quantitatively the rockfall risk for different cut slopes under unmitigated and mitigated conditions. The proposed methodology can estimate the risk reduction obtained using mitigation measures, such as introducing protections barriers, their periodic maintenance, and horizontal coverage ratio. This methodology was applied to 20 years of rockfall data collected by the Korea Expressway Corporation from 1215 artificial cut slopes along the highway network in South Korea. The rockfall frequency was analyzed based on the inventory data, and a rockfall hazard mitigation strategy was demonstrated using the suggested methodology for the case study. It was shown that appropriate mitigation strategies, based on number of protection barriers, interval of periodic maintenance, and horizontal coverage ratio, can be devised to reduce the risk of different artificial slopes below a target failure probability. The approach shown in this study can provide insights into ways of improving overall risk management to prevent losses by rockfall.