국토교통부는 2020년 '결빙 취약구간 평가 세부 배점표’에 따라, 전국의 고속국도와 일반국도를 대상으로 410개 구간의 결빙 취약구 간을 선정하였다. 그러나, 2021년 감사원의 결빙 취약구간 지정 적정성 감사 결과에서 감사원은 현재 지정ㆍ관리 중인 결빙 취약구간 및 결빙 취약구간 평가 세부 배점표의 적정성에 문제를 제기하였다. 이에, 국토교통부는 결빙 취약구간을 재지정하여 발표하였으나 그 에 대한 평가 및 지정 적정성 검증이 아직 이루어지지 않았다. 본 연구에서는 결빙 취약구간과 결빙사고 데이터의 위치정보를 수집하여 GIS(Geographic Information System) 데이터로 구축하고 맵핑(Mapping)하여 결빙 취약구간 내 결빙사고이력을 확인함으로서 결빙 취약구간의 결빙사고 예측성능을 평가하였다. 또한, 각 결빙 사고 발생지점에서 도로시설, 교통, 선형구조, 환경인자 데이터를 수집하여 분석한다. 이를 통해 결빙사고와 각 인자 간의 상관성을 파 악하고, 그 결과에 따라 결빙 취약구간 평가 세부 배점표의 평가항목 및 각 항목별 배점을 수정하고 보완함으로써 결빙 취약구간의 신뢰성을 제고한다.

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 : LED based Variable Message Signs(VMS) have been widely used to inform safety messages to the drivers in advance. Legibility Distance of VMS is the most important factor to provide the safety messages to drivers in timely and effective way. However, current National Standards on legibility distance design considers letter size only even there is a difficulty to read the signs at adverse weather conditions such as heavy fog. So, this study examined the legibility issue under fog by evaluating the legibility distance with two design factors such as letter size and luminance. METHODS : Two foggy weather conditions, intermediate and heavy fog, were simulated at real-road-scale Proving Ground. Legibility distance at daytime and nighttime was evaluated by test subjects. Subjects were asked to fill the legible distance on the test sheet and statistical significant was analysed at the lab. RESULTS : The legibility distance(LD) under fog was observed only 22 to 41% of LD observed under normal weather condition at daytime, and 26 to 45% at nighttime condition. Study results showed a consistent increase in LD with higher luminance even at same letter size and vice versa conditions, However, statically significant difference between groups was only revealed when both letter size and luminance level increased conditions. In order to apply the test results in terms of engineering benefits, LD results from significantly different groups was evaluated with relative to Stopping Sight Distance(SSD) within conceptual frame suggested in this study. CONCLUSIONS : From the study results, current National Standard on legibility distance design needs to consider letter size and luminance simultaneously to response the legibility issue in adverse weather conditions.

PURPOSES : This study aims to analyze the causes of pedestrian traffic accidents on community roads. METHODS : This study collected variables affecting pedestrian traffic accidents on community roads based on field surveys and analyzed them using negative binomial regression and zero-inflated negative binomial regression models. RESULTS : Model analysis results showed that the negative binomial regression model is more suitable than the zero-inflation negative binomial regression model. Additionally, the segment length (m), pedestrian volume (persons/15 min), traffic volume (numbers/15 min.), the extent of illegal parking, pedestrian-vehicle conflict ratio, and one-way traffic (one: residential, two: commercial) were found to influence pedestrian traffic accidents on community roads. Model fitness indicators, comparing actual values with predicted values, showed an MPB of 1.54, MAD of 2.57, and RMSE of 7.03. CONCLUSIONS : This study quantified the factors contributing to pedestrian traffic accidents on community roads by considering both static and dynamic elements. Instead of uniformly implementing measures, such as pedestrian priority zones and facility improvements on community roads, developing diverse strategies that consider various dynamic factors should be considered.

목적 : 본 연구는 시뮬레이터 훈련이 척수손상 환자의 운전시뮬레이터 도로 주행시간과 주행조작 능력에 미치는 영향을 알아보고자 하였다. 연구방법 : 본 연구는 단일사례실험연구 AB설계로 진행되었으며, 기초선 3회기, 중재기 10회기를 적용하였다. 기초선 3회, 중재기 5회 도로주행코스(중급) 수행 시 운전시간, 주행조작 능력 자료가 수집되었으며, 연구결과 분석을 위하여 시각적 분석 방법과 평균 ±2*표준 편차를 사용한 양적 분석을 동시에 사용하였다. 결과 : 연구대상자 3명의 총 주행시간은 기초선 A보다 중재기 B에서 3분 내외의 감소하였고, 세 명 모두에서 통계학적으 로 의미있는 주행 능력의 향상이 확인되었다. 주행조작능력 또한 오류 점수가 감소하였고, 첫 번째 참여자와 세 번째 참 여자의 경우 그 변화가 통계학적으로 유의하였다. 결론 : 본 연구에서 연구대상자의 총 주행시간 및 수행 오류의 감소가 확인되어 운전시뮬레이터 훈련의 효과가 있었다. 이 와 같은 결과는 운전시뮬레이터 훈련의 적용 가능성을 뒷받침 한다.

PURPOSES : This study predicts the concentration of suspended road dust (PM10) by analyzing meteorological, traffic, and atmospheric environmental data acquired at various angles, and attains a comprehensive understanding of the influencing factors of suspended road dust. METHODS : Experimental field methods were applied and statistical analyses were conducted. Field experiments were conducted using a vehicle-based measurement of suspended dust (PM10) to measure its concentration at the measurement site while maintaining a constant driving vehicular speed. Statistical analysis demonstrated the effects of the concentration of suspended dust on changes in meteorological and environmental factors and lanes per traffic volume at the time of measurement. Finally, a multiple linear regression model was applied to identify the factors which affected the generation of suspended dust. RESULTS : The analysis of suspended road dust concentrations according to the lanes per traffic volume and environmental factors showed that suspended dust concentrations increased at increasing driving speeds. In addition, the background concentration at the monitoring station was higher at high-wind speeds (>3.0 m/s) than at low-wind speeds (<1.6 m/s), but the suspended dust concentrations were higher at low-wind speeds. During the temperature inversion period from evening to morning, the suspended effects of traffic and meteorological factors were greater than the background concentration at the station. Multiple linear regression analysis showed that excluding yellow-dust days, which are known to affect atmospheric pollution levels, the accuracy of the model improved and resulted in increases in background PM10, vapor pressure, sea-level pressure, visibility, after-rainfall time, and in decreases in insolation and precipitation during low-wind speed conditions. CONCLUSIONS : At low-wind speeds, 5 days after rain, and when the relative humidity was higher than 72%, suspended dust was found to be higher than atmospheric PM10 concentration and may increase at increasing driving speeds and section lane traffic volumes. However, the volume of measured data in this study is limited to determining the patterns of suspended dust, as the silt loading of the operational road or the effects of prominent variables were not considered in this study. However, we identified prominent factors related to road-suspended dust for real-time road-dust predictions.

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, emissions from asphalt mixture production and construction processes are calculated and used to estimate the emission from each asphalt pavement layer. The calculated emissions for the processes are used as fundamental data to estimate the total emission from the entire life cycle of pavement engineering in South Korea. METHODS : A design proposal and the Korean standard, which provide quantitative information for activities, were used to estimate the amount of construction materials and energy consumption. Subsequently, the LCI DB from NAPA and the LCIA DB from EPA were utilized in conjunction with the estimated quantity to assess the effect of the emissions to determine their environmental impact categories. RESULTS : Calculation results show that 5.84 million ton of CO2eq is discharged from production and construction processes, whereas 3.24 million ton of CO2eq is discharged from operation processes in the pavement engineering sector. The total GHG emission, i.e., 9.08 million ton of CO2eq, is approximately 1.25% of the national GHG emission in 2018. The asphalt mixture production process results in the highest GHG emission in the life cycle of asphalt pavements. CONCLUSIONS : An LCI DB that accounts for the industrial characteristics of South Korea must be established to provide more reliable emission data to be used for national GHG reduction plans, including those for the pavement engineering sector.

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 : 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.

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.

PURPOSES : This study is performed first to define the aging of road facilities and to analyze the effects of environmental factors on the deterioration of median barriers. METHODS : The aging of road facilities is defined using an analytical hierarchy process (AHP). The first stage is associated with the period, facilities, and maintenance, whereas the second stage is associated with the details. The effects of environmental factors on the deterioration are analyzed by measuring the carbonation depth and compression strength. Two regions, i.e., Gangwon and Busan, are compared separately. Top, middle, and bottom samples are analyzed for both regions. RESULTS : Based on the result of the AHP analysis, weights for period (0.220), function (0.410), and maintenance (0.370) are derived. The average carbonation depths are 11.12 and 9.78 mm for Kangwon and Busan, respectively. The estimated values of compressive strength at Gangwon are 19.7 MPa (Wonju), 24.7 MPa (Samcheok A), and 25.9 MPa (Samcheok B), 20.2 MPa (Haeundae), 23.8 MPa (Yeongdo), and 29.5 MPa (Nam). CONCLUSIONS : The aging of road facilities is associated with subpar functionality and durability. Furthermore, the median barriers constructed in the Gangwon region deteriorated more significantly than those in the Busan region owing to environmental factors. In addition, the bottom samples are more affected by aging than the top samples.

PURPOSES : The purpose of this study is to investigate the effects of urban road characteristics on temperature changes in urban areas using surface thermal temperature. METHODS : This study measured the surface thermal temperature of each road component from urban roads, analyzed the effect of the road component characteristics and vegetation on temperature, and estimated the regression models. RESULTS : As a result, the mean temperature was 27.3 ℃ on the roadway, 25.5 ℃ on the vegetated median, and 22.9 ℃ on the sidewalks. The roadside temperature was 26.14 ℃ with surrounding buildings and 23.82 ℃ near green spaces. The temperature with street trees was lower (24.45 ℃) than without (28.38 ℃) while it was 23.96 ℃ with vegetated median and 25.64 ℃ without. The temperatures were lower (24.70 ℃) on the permeable surface than on the impermeable surface (28.38 ℃). Model estimates show that the temperature decreases by 0.007 ℃ with an increase of 1 m² green (permeable space) space and the temperature with buildings tends to be 1.729 ℃ higher than that with green space. As green space increases by 1 m², the temperature tends to decrease by 0.017 ℃ on the roadway and by 0.012 ℃ on the sidewalk. Shade effect models show that street trees with shade affect temperature reduction by -3.884 ℃ on roadways and -3.314 ℃ on sidewalks. CONCLUSIONS : The results of this study demonstrate the differing effects of road characteristics on temperature. The roadway is more sensitive than the sidewalk to temperature changes and roadside vegetation, ambient green space, and pavement permeability contribute to temperature reduction.

PURPOSES : This study analyzed explanatory variables, such as dangerous driving behaviors, in a negative binomial regression model, using the Digital Tachograph data of commercial vehicles, to assess the factors associated with freeway accidents. METHODS : Fixed parameter and random parameter negative binomial regression models were constructed using freeway accident data of commercial vehicles from January 2007 to July 2018 on the Gyeongbu Expressway from West Ulsan Interchange to Gimcheon Junction. RESULTS : Six explanatory variables (logarithm of average annual daily traffic, sunny, rainy, and snowy weather conditions, road curvature, and driving behaviors that included sudden stops) were found to impact the occurrence of freeway accidents significantly. Two of these variables (snowy weather conditions and sudden stops among dangerous driving behaviors) were analyzed as random parameters. These variables were shown as probabilistic variables that do not have a fixed impact on traffic accidents CONCLUSIONS : The variables analyzed as random parameters should be carefully considered when the freeway operating authorities plan an improvement project for highway safety.