PURPOSES : The primary purpose of this study is to develop a framework for predicting the demand and distribution of pedestrians when an open space zone is built at the top through the undergroundization of the Gyeongin Expressway. METHODS : After analyzing the current status through a survey on the number of people, students, surrounding traffic volume, and future socioeconomic indicators, the rate of change in the floating population and the rate of increase and decrease in the traffic volume of pedestrians were calculated to evaluate the effect. In addition, microscopic analysis results were derived by setting a pedestrian analysis zone (PAZ). A walking environment index (WEI) was developed that can quantitatively evaluate the degree of walking activation by indicating walking-related surrounding environmental factors. Based on this, a walking demand prediction model was developed. In addition, the results were validated by calculating the walking volume through a micro-simulation in/around the open space zone. RESULTS : The number of crosswalks and schools, transit development indicators, and pedestrian volume increased as the WEI value increased. However, the log form of the distance was observed to be a factor that reduced walking. CONCLUSIONS : This study attempted to reliably predict the demand for walking on the Gyeongin Expressway by calculating the amount of induced walking and the amount of passing walking. The pedestrian demand can be boosted by improving walking environments.

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.

In general, fire accidents in tunnels are sufficiently preventable, but the damage is very large. Therefore, the number of highway traffic accidents is high in spring when spring fatigue occurs and the traffic volume for maple travel increases. In particular, when analyzing the cause of death of people killed in fire accidents in tunnels, it is analyzed that most of them are suffocated by smoke. Therefore, in this study, it can be said that it is meaningful to make a social contribution to reduce the number of traffic accident deaths by establishing an efficient fire suppression system for fire accidents in tunnels.

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.

PURPOSES : In this study, a method for improving roadside barrier performance by introducing additional reinforcing materials without dismantling or drilling the old underperforming roadside barrier is developed based on the Installation and Management Guide for Roadside Safety Feature. METHODS : Reinforcing roadside barriers comprising reinforcement rails, impact absorbers, blockouts, and support reinforcement plates attached to an old underperformance roadside barrier were designed and manufactured. The manufactured prototypes were subjected to a vehicle crash test to verify their performance. RESULTS : In a structure whose performance is measurable after it collides with a large truck, the minimum strength of the structure to withstand the collision is maintained. Additionally, the safety of passengers measured via the collision test of a small vehicle is excellent. Hence, the reinforcement plan for the old underperforming roadside barrier satisfies all the performance evaluation standards. CONCLUSIONS : The cost of the improvement technology specifications proposed herein is approximately 50% lower than that of a SB3 level roadside barrier. The proposed method for improving the old underperforming roadside barrier is expected to be widely applied as it can be applied conveniently to road sites.

PURPOSES : A highway operates in a continuous flow and has restricted access. When an accident occurs on a highway, the impact on the traffic flow is large. In particular, an accident that occurs in a tunnel has a more significant impact than an accident that occurs in a general section. Accordingly, the management agency classifies the tunnel as a dangerous section and manages a tunnel of more than 1000 m using the Tunnel Transportation Management System. The purpose of this study was to select dangerous tunnels that require intensive management for the efficient management of highway tunnels. METHODS : In this study, for the selection of dangerous tunnels for expressways, all highway tunnels were classified into five clusters by characteristics. The traffic accident severity — equivalent property damage only (EPDO) — for each tunnel cluster was derived through a traffic accident analysis. Based on the severity analysis results, the safety performance function (SPF) for each cluster was established, and the accident risk tunnel was selected based on the potential safety improvement (PSI) value of each tunnel calculated using the empirical Bayes (EB) method for each tunnel cluster. RESULTS : As a result of the analysis, accident risk tunnels were selected based on the PSI values of the tunnels for each highway tunnel group. Finally, 55 hazardous tunnels were identified as hazardous tunnels: 13 tunnels in Cluster 1, 3 tunnels in Cluster 2, 15 tunnels in Cluster 3, 18 tunnels in Cluster 4, and 6 tunnels in Cluster 5. CONCLUSIONS : After classifying all 1232 tunnels on the highway into five clusters according to tunnel characteristics, EPDO analysis was performed for each tunnel cluster. To this end, the SPF for each cluster was constructed, and accident risk tunnels were selected based on the PSI value of each tunnel calculated using the EB method for each tunnel cluster. The tunnel cluster was classified as a typical tunnel type. As a result, most of the first and second values were calculated from cluster E (long tunnel cluster).

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 purpose of this study is to perform traffic flow characteristics analysis for each point of the long-term work zones and to propose an estimated capacity method to support the establishment of traffic flow management strategies for the long-term work zones. METHODS : The study explained the difference in traffic flow characteristics between the short-term and the long-term work zones, and estimated the capacity of the long-term work zones. The analysis data were collected from five points of long-term work zones of the twolane highway. And VDS and DSRC data were applied to validate data. RESULTS : The characteristics of traffic flow at each measurement point in the long-term work zones showed some differences, among which the capacity was estimated as the starting point to be 1,200 pcphpl and the ending point, 1,400 pcphpl. The delay length was estimated by applying the queuing theory based on the capacity of the start point where the bottleneck starts. As a result of verifying the congestion length based on space diagram map analysis, it was determined that the capacity calculation value and estimation methodology presented in this study were appropriate. CONCLUSIONS : The long-term work zones are mixed with different characteristics of roads, so as the capacity values depending on the analysis location. Therefore, it is necessary to select analysis points and methodologies for estimating capacity and delay depending on the purpose of the analysis, such as estimating the maximum queue length or analyzing the maximum travel time. Through this study, it is expected that by providing accurate information on congestion in advance, road users can detour to other roads, and construction officials can adjust the construction plan to minimize congestion in the construction section.

PURPOSES : In this study, we quantitatively prove the rubber necking phenomenon for highway traffic accidents and develop a calculation model based on the influencing factors. METHODS : Vehicle detector speed data in the opposite direction to the accident point were used based on the accident data on highways over the past three years, and a comparative verification was performed between nearby vehicle detector data to verify the reliability of the data. Accordingly, a binomial logistic model, ordinal probit regression model, and multilinear regression model were developed to compare the orientation. RESULTS : There was a difference in the influencing factors based on the dependent variable, and the day of the week, vehicle type, weather, longitudinal slope, and median height had an effect. Through a regression analysis, an influence coefficient was derived to calculate the driving speed deceleration value by rubbernecking. The results of the model analysis proved that the speed reduction caused by rubbernecking was more evident during the daytime than at night, during weekends compared to weekdays, and the speed reduction was more obvious for heavy vehicles compared to other types of vehicles. It can also be concluded that longer clearance time, higher accident severity, and higher traffic volume affect traffic delay. To verify the data and model equation, the mean prediction bias (MPB) and mean absolute deviation (MAD) were calculated for hundred cases randomly extracted from the collected accident data. These results were excellent. CONCLUSIONS : It can be developed into a human-engineered model that reflects various road/facility conditions, such as highways, other lanes, general roads, and roads without a median strip. This study is meaningful as a basic study on the quantitative effect of rubber necking.