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.

PURPOSES : The purpose of this study is to understand the effect of installing highway rest areas reflecting continuous driving time as a factor that can affect drowsy driving. METHODS : In this study, various models were tested for representing the effect of reducing accidents of highway rest areas. Among the various models including negative binomial, a series of the zero-inflated models reflecting accidents, the zero-inflated model showed the best suitability. RESULTS : According to the results of the zero inflated negative binomial model, installation of highway rest areas was found to have an accident reduction effect of approximately 11.93%. This is somewhat lower than the accident reduction effect estimated in previous studies. In addition, variables related to continuous driving time were found to affect accidents caused by drowsy driving. CONCLUSIONS : Basically, by using the continuous driving time index, a vehicle that has been driving continuously for more than 2 hours or if the continuous driving time is increased for more than 2 hours, the probability of accidents increases. However, in the case of trucks, a more in-depth study is needed on whether an increase in trucks induces defensive driving of other vehicles and this causes a reduction in accidents. Thus, it is necessary to use the variable cautiously for the highway rest area installation plan.

PURPOSES : The objective of this study is to develop an optimal placement of the overturning prevention device based on a 3D object model during the development of the girder-type overturning prevention device for the remote control construction of bridges METHODS : Based on existing construction methods and literature research, a detailed design model of a phase-optimized conduction prevention device is presented. The 3D-object model data, optimal placement, and an operating range of the equipment developed for the remote control construction of bridge girders were considered. RESULTS : The shape of the overturning prevention device was selected taking into account the dimensions and operating range of numerous devices developed for the remote control construction of the bridge. In particular, the detachable device was chosen to allow a trouble-free construction considering the spacing between the pier cap of the bridge and the girders. The overturning prevention device presented based on this 3D object model will be manufactured as a mock-up and used for a demonstration project on remote control bridge construction. CONCLUSIONS : This will enable easy and economical construction as this development will support remote control construction of bridge girders to avoid accidents such as workers falling from high places like piers.

PURPOSES : The surface distress of asphalt pavements is one of the major factors affecting the safety of road users. The aim of this study was to analyze the factors influencing the occurrence of surface distress and statistically predict its annual change to contribute to more reasonable asphalt pavement management using the data periodically collected by the national highway pavement data management system. METHODS : In this study, the factors that were expected to influence the surface distress were determined by reviewing the literature. The normality was secured by changing the forms of the variables to make the distribution of the variables got closer to normal distribution. In addition, min-max normalization was performed to minimize the effect of the unit and magnitude of the candidate independent variables on the dependent variable. The final candidate independent variables were determined by analyzing the correlation between the annual surface distress change and each candidate independent variable. In addition, a prediction model was developed by performing data grouping and multi-regression analysis. RESULTS : An annual surface distress change prediction model was developed using present surface distress, age, and below 0 ℃ days as the independent variables. As a result of sensitivity analysis, the surface distress affected the annual surface distress change the most. The positive correlation between the dependent variable and each independent variable demonstrated engineering and statistical meaningfulness of the prediction model. CONCLUSIONS : The surface distress in the future can be predicted by applying the annual surface distress prediction model to the national highway asphalt pavement sections with survey data. In addition, the prediction model can be applied to the national highway pavement condition index (NHPCI) evaluating the national highway asphalt pavement conditions to be used in the prediction of future NHPCI.

PURPOSES : The actual service life of repair methods applied to cement concrete pavement is analyzed based on de-icing agent usage. METHODS : Highway PMS data pertaining to de-icing agent usage are classified into three grades: low (1~5 ton/lane/year), medium (5~8 ton/lane/year), and high (greater than 8 ton/lane/year). The repair methods considered include diamond grinding, patching, joint repair, partial depth repair, and asphalt overlay on five major highways. The service life of each repair method is analyzed based on the usage level of the de-icing agent. RESULTS : The service lives of the applied repair methods are much shorter than expected. It is confirmed that the service life afforded by diamond grinding, patching, and joint repair methods are not significantly affected by the use of de-icing agents, whereas that afforded by asphalt overlay and partial depth repair methods is affected significantly. The service life afforded by the asphalt overlay and partial depth repair methods decreases at high usage levels of the de-icing agent (greater than 8 ton/lane/year). CONCLUSIONS : Among the repair methods considered, the service life afforded by partial depth repair and asphalt overlay is affected significantly by the amount of de-icing agent used. Additionally, the differences between the expected and actual analyzed service lives should be considered in the next-generation maintenance strategy for cement concrete pavements.

Driving safety of a semi-trailer is greatly reduced when driving in a section with a narrow turning radius, so a dynamic study of driving and road conditions is required. In this study, the driving stability of the semi-trailer was investigated using the RecurDyn program in consideration of the velocity and weight of the semi-trailer in the entrance curve section of the highway, and the turning angle and radius of the curved road. In order to select the model and analysis conditions according to the road type, the sloping curved road was modeled by selecting the curvature, entry length, height difference, and entrance angle of the curved section. From the analysis results, the higher the semi-trailer's entrance velocity, the heavier the weight, the narrower the entrance angle of the curved road, and the smaller the curvature, the greater the semi-trailer's maximum running angular speed which had an effect on driving stability.

PURPOSES : Rut depth of asphalt pavements is a major factor that affects the maintenance of pavements as well as the safety of drivers. The purpose of this study was to analyze the factors influencing rut depth, using data collected periodically on national highways by the pavement management system and, consequently, predict annual rut depth change, to contribute to improved asphalt pavement management. METHODS : The factors expected to influence rut depth were determined by reviewing relevant literature, and collecting the related data. Further, the correlations between the annual rut depth change and the influencing factors were analyzed. Subsequently, the annual rut depth change model was developed by performing regression analysis using age, present rut depth, and annual average maximum temperature as independent variables. RESULTS : From the sensitivity analysis of the developed model, it was found that age affected the annual rut depth change the most. Additionally, the relationship between the dependent and independent variables was statistically significant. The model developed in this study could reasonably predict the change in the rut depth of the national highway asphalt pavements. CONCLUSIONS : In summary, it was verified that the model developed in this study could be used to predict the change in the National Highway Pavement Condition Index (NHPCI), which represents comprehensive conditions of national highway pavements. Development of other models that predict changes in surface distress as well as international roughness index is required to predict the change in NHPCI, as they are the independent variables of the NHPCI prediction model.

The prospect of the highway traffic road construction has led to resistance from residents, partly based on noise and vibration issues. Particularly, as tracks often pass closely to residential dwellings, constructors are then required to take account of noise and vibration. So the prediction of noise and vibration for highway traffic is very important thing. The highway traffic noise and vibration make one specific issue. For the highway traffic road, this paper concerns the noise by the wheel/tire and the structure-borne noise by the road. Based on the results, this paper proposes the source model of highway traffic noise and the calculation model for highway traffic noise. Also prediction model is presented with traffic noise which are calculated by considering the power level of a source for one-third octave band, ground absorption and barrier deflection. A lot of empirical data is needed to predict the noise and vibration. And one of the best ways to control the wayside noise is to analyze the noise level.

PURPOSES : This study focuses on advance traffic information to prevent secondary traffic accidents on express highways. The purpose of this study is to analysis the optimal scenario by evaluating the effect of each advance traffic information scenarios using virtual driving simulation. METHODS : By designing traffic information scenarios and services with a combination of VMS and mobile PUSH notifications, driver behavior in the event of a traffic accident was analyzed. For this, a simulation environment was designed through engineering analysis. Through virtual driving simulation, the driver's deceleration point and the perception-reaction time are analyzed. RESULTS : Four scenarios were designed and reviewed so that VMS and mobile PUSH notification can be provided simultaneously after the driver drove for 5 km. As a result of driving with 30 drivers, the drivers reacted fastest when VMS was installed, followed by mobile PUSH notification, VMS+mobile PUSH notification, and NOTHING. CONCLUSIONS : When designing traffic information service, it was observed that providing information through VMS alone is more efficient than providing two services of traffic information. Therefore, it can be used as basic data for preventing secondary accidents on express highway.

PURPOSES : The purpose of this study was to analyze the effect of reducing nitrogen oxide concentration in a photocatalyst (titanium dioxide) using statistical methods such as the Anderson-Darling test. METHODS : To compare and analyze the effect of reducing the nitrogen oxide concentrations in titanium dioxide, titanium dioxide was applied to the public road, and data acquisition in terms of nitrogen oxide concentration was conducted from roads with/without applying titanium dioxide (test section and reference section, respectively). Then, the probabilities of occurrence of nitrogen oxide concentrations in the test and reference sections were estimated and compared using the Anderson-Darling test. RESULTS : According to the comparison and analysis of probabilities in the nitrogen oxide concentration of the test and reference sections, the probabilities of nitrogen oxide concentration on December 4th were estimated as ‘High’ (17.5%, 37.9%), ‘Moderate’ (30.5%, 40.8%), and ‘Low’ (52.0%, 21.3%), respectively, and on December 5th, as ‘High’ (20.6%, 39.1%), ‘Moderate’ (26.2%, 33.0%), and ‘Low’ (53.2%, 27.9%), respectively. In addition, the probabilities of nitrogen oxide concentration in the test and reference sections were analyzed on December 6th as ‘High’ (16.5%, 36.8%), ‘Moderate’ (27.9%, 38.5%), and ‘Low’ (55.6%, 24.8%), respectively. CONCLUSIONS : Based on the results of this study, in the test section with application of titanium dioxide, the nitrogen oxide concentration was found to have a low probability, and in the reference section, the nitrogen oxide concentration was found to be higher than that in the test section. Therefore, it can be concluded that titanium dioxide applied to road facilities has a nitrogen oxide reduction effect.

PURPOSES : In this study, drone highway route alternatives were evaluated using the analytic hierarchy process (AHP) technique to investigate any difficulties or improvements while designing drone highway routes. METHODS : Based on the literature review and AHP analysis, 39 road and airport experts were surveyed to evaluate two alternate drone highway routes that connect the Seoul train station and Jamsil park near Gangnam business district. RESULTS : The AHP analysis results revealed that the environmental aspect was the most critical factor in designing a drone highway route, followed by social and technological factors. Among the investigated factors, noise and life-environment showed the highest geometric mean value of 0.21. This mean should be considered when developing plans and policies for drone highway design. CONCLUSIONS : Environmental and social agreement is more crucial than the technological and economic aspects when designing drone highway routes. Laws and policies should be updated and followed to support the drone highway system, which is vital in logistics.

PURPOSES : The purpose of this study is to contribute to the utilization of standards while considering the possible upgrade of a local system as a subject of the application. Therefore, this study aims to explore the possible application of LandInfra for a local road management (maintenance) system in the context of enabling the basis of 3D geospatial road information management in Korea. METHODS : Based on a review of related literature and international standards, an analysis of the current system is performed. After reviewing the LandInfra standard, an examination of corresponding classes between each data model (HMS and LandInfra) is performed for the mapping process. After the mapping process, a data model of the LandInfra-based HMS pavement data model is proposed. RESULTS : To apply the LandInfa to the HMS pavement part, an examination of each data model is performed. After this procedure, a LandInfra-based HMS pavement database schema is proposed in the context of enabling 3D geospatial road information management and maintenance, particularly for pavement management information. CONCLUSIONS : This paper presents how the LandInfra international open geospatial standard can be applied to the local road management system (HMS pavement part). As a result of this study, the LandInfra standard could be applied to the HMS; however, an encoding of the standard is required for conformance. Thus, further studies would be the encoding of the proposed data model for conformance with InfaGML encoding standards. In addition, a system prototype may be needed for complete application.

PURPOSES : The purpose of this study is to disseminate the process of deriving the truck performance curve of Korea’s representative trucks in detail such that the relevant experts can use it in the future when re-selecting the representative trucks and deriving the truck performance curve accordingly. METHODS : To collect relevant data required to derive the truck performance curve, this study used four trucks that implemented the weight/power of the nation’s representative trucks, and conducted a practical driving test on four different upgrade sections. RESULTS : The truck performance curve was derived for each driving position to represent the deceleration and acceleration capabilities of the truck through the actual driving test on the upgrade sections. CONCLUSIONS : The truck performance curve derived from this study indicated that the truck’s deceleration and acceleration capabilities increased as the total weight/power of Korea’s representative trucks improved, and the design of the climbing lane demonstrated that the design method used in this study saved approximately 60% of the construction cost compared to the existing method.

PURPOSES : Despite the availability of larger traffic data and more advanced data collection methods, the problem of missing data is yet to be solved. Imputing missing data to ensure data quality and reliability of statistics has always been challenging. Missing data are imputed via several existing methods, such as autoregressive integrated moving average, exponential smoothing, and interpolation. However, these methods are complicated and results in significant errors. METHODS : A deep-learning method was applied in this study to impute traffic volume data of the South Korean national highway. Traffic data were trained using the long short-term memory method, which is a suitable deep-learning method for time series analysis. RESULTS : Three cases were proposed to estimate the traffic volume. In the first case, which represented the general conditions, the mean absolute percentage error (MAPE) was 12.7%. The second estimation case, which was based on the opposite traffic flow, exhibited a MAPE of 17%~18%. The third case, which was estimated using adjacent-section data, had a MAPE of 18.2%. CONCLUSIONS : Deep learning may be a suitable alternative data imputation method based on the limited site and data. However, its application depends on the specific situation. Furthermore, deep-learning models can be improved using an ensemble method, batch-size, or through model-structure optimization.