• Journal of Korean Society of Water and Wastewater
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• v.20 no.6
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.31-43
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• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.1-12
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• 2010

This paper deals with the transmission interval of vehicle data in smart highway where WAVE (Wireless Access for Vehicular Environments) systems have been installed for advanced road infrastructure. The vehicle data could be collected at every second, which is containing location information of the vehicle as well the vehicle speed, RPM, fuel consuming and safety data. The safety data such as DTC code, can be collected through OBD-II. These vehicle data can be used for valuable contents for processing and providing traffic information. In this paper, we propose a model to decide the collection interval of vehicle information in real time environment. This model can change the transmission interval along with special and time-variant traffic condition based on the 32 scenarios using microscopic traffic simulator, VISSIM. We have reviewed the transmission interval, communication transmission quantity and communication interval, tried to confirm about communication possibility and BPS, etc for each scenario. As results, in 2-lane from 1km highway segment, most appropriate transmission interval is 2 times over spatial basic segment considering to communication specification. In the future, if a variety of wireless technologies on the road is introduced, this paper considering not only traffic condition but also wireless network specification will be utilized the high value.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.86-96
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• 2010

In this paper, we propose stereo vision-based obstacle detection and vehicle verification methods using U-disparity map and bird's-eye view mapping. First, we extract a road feature using maximum frequent values in each row and column. And we extract obstacle areas on the road using the extracted road feature. To extract obstacle areas exactly we utilize U-disparity map. We can extract obstacle areas exactly on the U-disparity map using threshold value which consists of disparity value and camera parameter. But there are still multiple obstacles in the extracted obstacle areas. Thus, we perform another processing, namely segmentation. We convert the extracted obstacle areas into a bird's-eye view using camera modeling and parameters. We can segment obstacle areas on the bird's-eye view robustly because obstacles are represented on it according to ranges. Finally, we verify the obstacles whether those are vehicles or not using various vehicle features, namely road contacting, constant horizontal length, aspect ratio and texture information. We conduct experiments to prove the performance of our proposed algorithms in real traffic situations.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.589-599
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• 2021

Purpose: A reliable indicator of congested traffic speed is essential in providing the information of traffic flow states about motorway sections. The aim of this study is to propose an adaptive indicator of congested speed which is employed for deciding the traffic flow states for individual motorway sections using disaggregated section-based speed data. Method: Typically, the state of traffic flow is categorized into the three: uncongested, mixed, congested states. A method, presented in this study, was developed for identifying boundary speed values of road sections through categorizing the three traffic flow states with individual vehicular speed values. The boundary speed state of each road segment is determined using the speed distributions of mixed and congested traffic states. Result: Analysis results revealed that boundary speed values between mixed and congested states for road sections were similar to those of US and EU criteria (i.e., 48.28~66.0 kph). This indicates that boundary speed values could be different according to road sections. Conclusion: It is expected that the method and indicator, proposed in this study, could be efficaciously used for providing ad-hoc real-time traffic states and computing traffic congestion costs for motorway sections in the era of big data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.89-97
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• 2013

Recently, economic and social damages are globally increased due to the heavy snowfall caused by global warming. To reduce the damages of sudden regional heavy snow in roads, suitable countermeasures should be established based on the accurate detection of snowfall intensity for each roadway segment. In this paper, we deal with snowfall intensity detecting algorithm in the road area from CCD Imagery. First, we determine the MLZ (MotionLess Zone), which does not contain lane markings and moving cars, in the image space. Next, snow streaks trespassing the MLZ are extracted with Canny operator and proposed algorithm. Also, the concept of SII (Snow Intensity Index), which is the number of snow streaks during one minute in the MLZ, is defined. Finally, the effectiveness of proposed algorithm is proved by visually comparing the imagery and SII value obtained during 69 minutes. In consequence, we figured out that the integration of SII is significantly related to an actual amount of snowfall.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.745-756
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• 2013

The purpose of this study is to evaluate representativeness of fuel-based emission factors. Twelve light-duty diesel vehicles which meet Euro-3 to 5 legislative emission limits were selected for emission tests. Second-by-second modal emission rates of vehicles were measured on a standard laboratory chassis dynamometer system. An off-cycle driving cycle was developed as a representative Korean real-world on-road driving cycle. Fuel-based emission factors were developed for short trip segments that involved in the selected driving cycle. Each segment was defined to have unit travel distance, which is 1 km, and characterized by its average speed and Relative Positive Acceleration (RPA). Fuel-based $NO_x$ emission factors demonstrate relatively good representativeness in terms of vehicle operation conditions. $NO_x$ emission factors are estimated to be within ${\pm}20%$ of area-wide emission factor under more than 40% of total driving situations. This result implies that the fuel-based $NO_x$ emission factor could be practically implemented into the on-road emission management strategies, such as a remote sensing device (RSD). High emitting vehicles as well as high emitting operating conditions heavily affect on the mean values and distributions of CO and THC emission factors. Few high emitting conditions are pulling up the mean value and biasing the distributions, which weaken representativeness of fuel-based CO and THC emission factors.

• International Journal of Highway Engineering
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• v.2 no.4 s.6
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• pp.111-122
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• 2000

PMS(Pavement Management System) has been developed and/or operated for the freeway and national highway systems in Korea. There is, however, no municipal PMS that is necessary in many cities for efficient management of their roadways. In this study, a municipal Prototype PMS is developed. The Prototype PMS is designed to be operated on PC base. It uses GIS interface for user friendliness that applies color graphics, text and distress pictures to display pavement conditions and rehabilitation information for both current and historical situations. The computer program of the prototype PMS consists of four major functions(inquiry, analysis, data management, and print). Especially, prioritization and M&R(Maintenance and Rehabilitation) alternative selection procedure is designed to be flexible so that the users can modify the decision criteria whenever it is necessary. Database items of the Prototype PMS is carefully selected for the objectives and size of municipal PMS. Reference point method is basically used for the location referencing in the Database. The unit section consists of each loom segment of the road for effective management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.765-773
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• 2009

Currently Telematics traffic information services have been various because we can collect real-time traffic information through Intelligent Transport System. In this paper, we proposed and implemented a short-term traffic information prediction model for giving to guarantee the traffic information with high quality in the near future. A Short-term prediction model is for forecasting traffic flows of each segment in the near future. Our prediction model gives an average speed on the each segment from 5 minutes later to 60 minutes later. We designed a Bayesian network for each segment with some casual nodes which makes an impact to the road situation in the future and found out its joint probability density function on the supposition of GMM(Gaussian Mixture Model) using EM(Expectation Maximization) algorithm with training real-time traffic data. To validate the precision of our prediction model we had conducted various experiments with real-time traffic data and computed RMSE(Root Mean Square Error) between a real speed and its prediction speed. As the result, our model gave 4.5, 4.8, 5.2 as an average value of RMSE about 10, 30, 60 minutes later, respectively.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.221-227
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• 2008

This study identifies the relationship between traffic data quality obtained from loop detectors and their location. Traffic data basically shows traffic flow conditions and thus, these information can be used as inputs for various transportation management strategies. Out study presents how to determine optimal downstream detector location on merging area in order to enhance the effects of ramp metering strategies. Microscopic simulation model, PARAMICS, is used as the main analytical tool. Assuming that detector location relies heavily on traffic flow characteristics in each roadway segment, we perform statistical analysis to identify homogeneous traffic conditions on merging area.