• International Journal of Highway Engineering
• /
• v.7 no.3 s.25
• /
• pp.43-52
• /
• 2005

Highway classification is an essential part of defining design criteria of roads. This study is to classify highways by factor analysis. To accomplish the objectives, factor analysis is performed for classifying highways using the traffic data observed at the permanent traffic count points in 2004. A total off variables are applied : AADT, K factor, D factor, heavy vehicle proportion, day time traffic volume proportion, peak hour volume proportion, sunday factor, vacation factor and COV(Coefficient of Variation). The results of factor analysis show that variables are divided into two factors, which are the factor related to the fluctuational characteristics of traffic volume and the factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, 353 permanent traffic count points are categorized into such three groups as type I for urban highway, type II for rural highway, type III for recreational highway, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.6D
• /
• pp.759-766
• /
• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.

• Journal of Korean Society of Transportation
• /
• v.28 no.5
• /
• pp.155-162
• /
• 2010

Elderly pedestrians account for more than 30% of all deaths in traffic accident and the number of elderly-related traffic accidents are increasing every year. Considering Korea's quickly aging society, drastic measures must henceforth be taken. Taking notice of the elderly living in and moving around the provinces, this research focused on analyzing the characteristics of elderly pedistrians' traffic accidents on provincial roads and developing an Equivalent Property Damage Only (EPDO) model. The authors collected 720 traffic accident data points from the police agency and developed the EPDO model, weighted differently by light injury, severe injury, and death using Multiple Regression Analysis. As a result, the speed of vehicles is the most influential variable in EPDO, and the shape of the road is significant as well. Therefore, various policies should be established like improving the environmental factors of provincial roads, like expanding speed-reduction treatments and signage, and setting up detours around areas of high elderly concentration.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.2
• /
• pp.10-20
• /
• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.3
• /
• pp.26-35
• /
• 2013

According to traffic accidents-related statistics, 57.6 percent of the fatality of vehicle-to-pedestrian accident, occurred on crosswalk in rural highways. Ministry of Land, Transport and Maritime Affairs in South Korea is conceiving to reduce in the number of the fatality. This study is to reestablish the criteria of implementing lighting through field experiments and to develop an effective alternative of crosswalk lighting.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.2
• /
• pp.48-56
• /
• 2012

One kind of crowdsourcing techniques which allow drivers to collect and provide traffic information using smartphones and applications is being introduced to ITS system as well. The introduction of crowdsourcing techniques requires changes in the existing ITS based on Insourcing which provide traffic information generated by detectors through VMS. ITS Information have had two problems, one is the high cost and the other is an interrupted service. Experts expect crowdsourcing technique which is created SNS, will overcome problems of ITS. But, there are not many examples and research results. Crowdsourcing technique was utilized in Jeju ATMS project to install ITS on the coastal round roads around Jeju since ITS to install point detectors turned out to be non-economic method in case of the coastal round roads with low traffic volume. However, there existed links in which traffic information cannot be generated as there were no smartphone users (crowds) even in the cost-effective crowdsourcing techniques, which indicates the fact that the crowdsourcing method is suitable for urban roads with many smartphone users, but not for local minor roads. On the contrary, insourcing-based ITS is considered to be non-economic method in applying to all roads in the city, but it can be effectively utilized in the local minor roads. Accordingly, Inter-sourcing based ITS operating system in which insourcing is connected with crowdsourcing was suggested in this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.3
• /
• pp.19-28
• /
• 2013

This study evaluated the quantitative effects of the deployment of semi-actuated signal systems using field data. For this, a semi-actuted signal system was deployed in the regional roadway network extensively. This paper investigated an operating strategy of semi-actuated signal systems for field application, and implemented the functional strategy into the standard signal controller. The performance was evaluated using three measures of effectiveness such as traffic volume, travel time, and the number of delayed vehicle. From the analysis results, traffic volume increased about 9.4% and 11.3% for morning and evening peak periods, respectively. The average travel time was reduced about 6.3% and 7.8% during morning and evening peak periods, respectively because of the expansion of bandwidths for major streets. In addition, the number of delayed vehicles was reduced about 36.4% and 23.9% for morning and evening peak periods, respectively. It is expected that the effectiveness of signal control system can be improved by incorporating a properly designed semi-actuated signal system in regional roadways with directional demand variation.

• Journal of Korean Society of Transportation
• /
• v.34 no.2
• /
• pp.123-134
• /
• 2016

Traffic accident at intersections takes 44.3% of total number of accidents on entire road network of Korea in 2014. Although several studies addressed contributory factors of accidents at signalized intersection, very few is known about the factors at rural unsignalized intersections. The objective of this study is therefore to investigate specific characteristics of crashes at rural unsignalized intersection and to identify contributory factors in causing crashes by statistical approach using the Ordered Logistic Regression Model. The results show that main type of car crashes at unsignalized intersection during the daytime is T-bone crashes and the number of crashes at 4-legged intersections are 1.53 times more than that at 3-legged intersections. Most collisions are caused by negligence of drivers and violation of Right of Way. Based upon the analysis, accident severity is modeled as classified by two types such as 3-legged intersection and 4-legged intersection. It shows that contributory factors in causing crashes at rural unsignalized intersections are poor sight distance problem, average daily traffic, time of day(night, or day), angle of intersection, ratio of heavy vehicles, number of traffic violations at intersection, and number of lanes on minor street.

• International Journal of Highway Engineering
• /
• v.9 no.3
• /
• pp.1-12
• /
• 2007

Roads in Korea can be classified into four types according to their responsible authorities. For example, Motorway is constructed, managed, and operated by the Korea Highway Corporation. Ministry of Construction and Transportation is in charge of National Highway, and Province Roads are run by each province government. Urban/county Roads are run by corresponding local government. This study analyses the trends of road accidents for each road type. For this purpose, the numbers of accidents, fatalities, and injuries are compared for each road type for last 15 years. The result shows that Urban/County Roads are the most dangerous, while Motorways are the safest, when we simply compare the numbers of accidents, fatalities, and injuries. However, when we compare these numbers by dividing by total road length, National Highway becomes the most dangerous while Province Roads becomes the safest. In the case of road accidents, fatalities, and injuries per vehicle km, which is known as the most objective comparison measure, it turns out that National Highway is the most dangerous roads again. This study also developed time series models to estimate trends of fatalities for each road type. These models will be useful when we set up or evaluate targets of national road safety.

• Journal of Korean Society of Transportation
• /
• v.33 no.6
• /
• pp.554-563
• /
• 2015

This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.