• International Journal of Highway Engineering
• /
• v.18 no.4
• /
• pp.19-28
• /
• 2016

PURPOSES : Long-life asphalt pavements are used widely in developed countries. In order to be able to devise an effective maintenance strategy for such pavements, in this study, we evaluated the performance of the long-life asphalt pavements constructed along the national highways in South Korea. Further, an economic evaluation of the long-life asphalt pavements was performed based on a life-cycle cost analysis. We aimed to devise a model for evaluating the performance of long-life asphalt pavements using the national highway pavement management system (PMS) database as well as for analyzing the economic feasibility of such pavements, in order to promote their use in South Korea. METHODS : The maintenance history and pavement performance data were obtained from the national highway PMS database. The pavement performances for a total of 292 sections of 10 lanes (5 northbound lanes and 5 eastbound lanes) of national highways were used in this study. Models to predict the performances of hot mix asphalt (HMA) and long-life asphalt pavements under two distinct traffic conditions were developed using a simple regression method. Further, the economic feasibility of long-life asphalt pavements was evaluated using the Korea Pavement Management System (KoPMS). RESULTS : We developed service-life prediction models based on the traffic volume and the equivalent of single-axle load and found that long-life asphalt pavements have service lives 50% longer than those of HMA pavements. Further, the results of the economic analysis showed that long-life asphalt pavements are superior in terms of various economic indexes, including user cost, delay cost, total cost, and user benefits, even though their maintenance cost is higher than that of HMA pavements. A comparison of the economic feasibilities of the various groups showed that group A is superior to HMA pavements in all aspects except in terms of the maintenance criterion (crack 20% or higher) as per the NPV index. However, the long-life asphalt pavements in group B were superior in terms of the maintenance criterion (crack 25% or higher) regardless of the economic feasibility. CONCLUSIONS : The service life of long-life asphalt pavements was found to be approximately 50% longer than that of HMA pavements, regardless of the traffic volume characteristics. The economic feasibility of long-life asphalt pavements was evaluated based on the KoPMS. The results of the economic analysis were the following: long-life asphalt pavements are exceptional in terms of almost all factors, such as user cost, delay cost, total cost, and user benefit; however, the exception is the maintenance cost. Further, the economic feasibility of the long-life asphalt pavements in group B was found to be better than that of the HMA pavements (crack 25% or higher).

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.6
• /
• pp.606-614
• /
• 2020

In this paper, we analyze the influences of ship traffic and marine weather information on underwater ambient noise. Ambient noise is an important environmental factor that greatly affects the detection performance of underwater sonar systems. In order to implement an automated system such as prediction of detection performance using artificial intelligence technology, which has been recently studied, it is necessary to obtain and analyze major data related to these. The main sources of ambient noise have various causes. In the case of sonar systems operating in offshore seas, the detection performance is greatly affected by the noise caused by ship traffic and marine weather. Therefore, in this paper, the impact of each data was analyzed using the measurement results of ambient noise obtained in coastal area of the East Sea of Korea, and public data of nearby ship traffic and ocean weather information. As a result, it was observed that the underwater ambient noise was highly correlated with the change of the ship's traffic volume, and that marine environment factors such as wind speed, wave height, and rainfall had an effect on a specific frequency band.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.2D
• /
• pp.137-145
• /
• 2012

According to the National Police Agency, the total number of traffic accidents which occurred in 2010 was 226,878. Intersection accidents accounts for 44.8%, the largest portion of the entire traffic accidents. An research on the signalized intersection is constantly made, while an research on the unsignalized intersection is yet insufficient. This study selected traffic volume, road width, and sight distance as the input variables which affect unsignalized intersection accidents, and number of accidents as the output variable to build a model using ANFIS(Adaptive Neuro-Fuzzy Inference System). The forecast performance of this model is evaluated by comparing the actual measurement value with the forecasted value. The compatibility is evaluated by R2, the coefficient of determination, along with Mean Absolute Error (MAE) and Mean Square Error (MSE), the indicators which represent the degree of error and distribution. The result shows that the $R^2$ is 0.9817, while MAE and MSE are 0.4773 and 0.3037 respectively, which means that the explanatory power of the model is quite decent. This study is expected to provide the basic data for establishment of safety measure for unsignalized intersection and the improvement of traffic accidents.

• Journal of Navigation and Port Research
• /
• v.38 no.1
• /
• pp.65-71
• /
• 2014

Gyeongbu and Namhae expressways in the country, are the major arterial highways which are connected with the Busan port in the north-south and east-west directions, respectively, and required to study the traffic characteristics about the hourly volume factors(K-factor) by concentrated midium-size and large-size cargo trucks of 20% or higher in expressways. We therefore attempted to predict the K-factor in expressways through the correlation analysis between K-factor and K-factor estimates on the basis of the short-term VDS data collected at the basic segments of the above major expressways. As a result, power model appeared to be appropriate in predicting K-factor by the K-factor estimate based on VDS data for 7 days with a high explanatory power and validity.

• International Journal of Highway Engineering
• /
• v.17 no.3
• /
• pp.69-76
• /
• 2015

PURPOSES : Performance evaluation of four types of asphalt concrete overlays for deteriorated national highways. METHODS : Pavement distress surveys for crack rate and rut depth have been conducted annually using an automated pavement survey vehicle since 2007. Linear and non-linear performance prediction models of the asphalt concrete overlays were developed for 43 sections. The service life of the asphalt overlays was defined as the number of years after which a crack rate of 30% or rut depth of 15mm is observed. RESULTS : The service life of the asphalt overlays was estimated as 17.4 years on an average. In 90.7% of the sections, the service life of the overlays was 15 years or more which is 1.5 times the life of conventional asphalt concrete overlays used in national highways. The performance of the overlays was dependent on the type of asphalt mixture, traffic volume levels, and environmental conditions. CONCLUSIONS : The usage of stone mastic asphalt (SMA) and polymer-modified asphalt (PMA) for the overlays provided good resistance to cracking and rutting development. It is recommended that appropriate asphalt concrete overlays must be applied depending on the type of existing pavement distress.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.6
• /
• pp.607-620
• /
• 1998

The influence of transportation on air quality has been elevating in urban area. Air pollutants from automobiles cause primary and secondary air pollution, and need to be tightly controlled. In this study, the effect of automobile air pollutants on highway vicinity area was evaluated by the comparison of field measurement. and target was for modeling using CALINE3, NO2 was the target for this work. It was found that the concentration predicted by CALINE3 is overestimated at low wind speed and input data of wind speed requires correction. Based on the measured data, the wind speed was modified by effective wind speed equation [Ue=U+0.24·EXP(-pxU)], and there after the accuracy of CALINE3 calculation was improved neighborhood area of highway. It was also observed that weather conditions and traffic volume affect the concentration of air pollution. Finally, the NO2 effect of automobile air pollutants on the vicinity area of highway proved to be up to 400∼600m from the highway.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.19 no.3
• /
• pp.211-217
• /
• 2001

Chun-chon city is the area that is estimated to be damaged by breaking of Dam by a flood among several natural disaster. If so, what is the way that minimize the damage\ulcorner There are many ones but it may be best that we take shelter from it before the breaking of Dam. Then when must we do\ulcorner By what instrument can we minimize the damage of people. And how do we compute the time\ulcorner In this study, using buffering, overlap and network, GIS ability based on ARC/INFO. I chose six routesto take shelter outside of Chun-chon city, calculated the traffic volume of each ones, and estimated the time for decentralization of risks.

• International Journal of Highway Engineering
• /
• v.16 no.5
• /
• pp.99-108
• /
• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• International Journal of Highway Engineering
• /
• v.14 no.6
• /
• pp.131-138
• /
• 2012

PURPOSES : Two-lane highways have one lane in each direction, and lane changing and passing maneuvers take place in the opposing lane depending on the availability of passing sight distance. 2001 Korea Highway Capacity Manual (KHCM) is classified into two classes of two-lane highways (Type I, II), and average travel speed and time-delayed rate are used as measures of effectiveness (MOEs). However, since existing two-lane highways have both uninterrupted and interrupted traffic flow-system elements, a variety of free-flow speeds exhibits in two-lane highways. In addition, it is necessary to check if the linear-relationship between volumes and time-delayed rate is appropriate. Then, this study is to reestablish the relationship between average travel speed, time-delayed rate, and flow. METHODS : TWOPAS model was selected to conduct this study, and the free-flow speeds of passenger cars and the percentage of following vehicles observed in two-lane highways were applied to the model as the input. The revised relationships were developed from the computer simulation. RESULTS : In the revised average travel speed vs. flow relationship, the free-flow speed of 90km/h and 70km/h were added. It shows that the relationship between time delayed-rate and flow appeared to be appropriate with the log-function form and that there was no difference in time-delayed rate between the free flow speeds. In addition to revise the relationships, the speed prediction model and the time-delayed rate prediction model were also developed. CONCLUSIONS : The revised relationships between average travel speed, time-delayed rate, and flow would be useful in estimating the Level of Service(LOS) of a two-lane highway.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.861-866
• /
• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.