• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1523-1526
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• 2002

기존의 길 안내시스템은 지리정보시스템(GIS)와 무선데이터통신을 이용하여 목적지까지의 길을 음성과 지도로 안내하는 서비스였다. 이는 지리정보처리 장치 또는 마이크로 브라우저 등을 설치해야만 길 안내 등의 교통안내가 가능했었다. 본 논문에서는 이동형 단말기 또는 휴대폰에서 전기의 장치나 시스템을 필요로 하지 않아도 가능한 시스템을 제시하였고, 일반전인 전화 또는 전자메일 송신만으로 길 안내 처리가 가능하게 하였다.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.201-213
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• 2018

In recent years, the number of traffic accidents caused by car accidents has been decreasing steadily due to traffic accident prevention activities in Korea. However, the number of accidents in Seoul is higher than that of other regions. Various studies have been conducted to prevent traffic accidents, which are human disasters. In particular, previous studies have performed the spatial analysis of traffic accidents by counting the number of traffic accidents by administrative districts or by estimating the density through kernel density method in order to identify the traffic accident cluster areas. However, since traffic accidents take place along the road, it would be more meaningful to investigate them concentrated on the road network. In this study, traffic accidents were assigned to the nearest road network in two ways and analyzed by hotspot analysis using Getis-Ord Gi* statistics. One of them was investigated with a fixed road link of 10m unit, and the other by computing the average traffic accidents per unit length per road section. As a result by the first method, it was possible to identify the specific road sections where traffic accidents are concentrated. On the other hand, the results by the second method showed that the traffic accident concentrated areas are extensible depending on the characteristic of the road links. The methods proposed here provide different approaches for visualizing the traffic accidents and thus, make it possible to identify those sections clearly that need improvement as for the traffic environment.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.715-724
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• 2010

Recurrent event data occurs when a subject experience the event of interest several times and has been found in biomedical studies, sociology and engineering. Several diverse approaches have been applied to analyze the recurrent events (Cook and Lawless, 2007). In this study, we analyzed the YTOP(Young Traffic Offenders Program) dataset which consists of 192 drivers with conviction dates by speeding violation and traffic rule violation. We consider a subject-specific effect, frailty, to reflect the individual's driving behavior and extend to time-varying frailty effect. Another feature of this study is about the redefinition of risk set. During the study, subject may be under suspension and this period is regarded as non-risk period. Thus the risk variables are reformatted according to suspension and termination time.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.541-551
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• 2009

Generalized processor sharing(GPS) service policy is a scheduling algorithm to allocate the bandwidth of a queueing system with multi-class input traffic. In a queueing system with single-class traffic, the stationary queue length becomes larger stochastically when the bandwidth (i.e. the service rate) of the system decreases. For a given GPS server, we consider the similar problem to this. We define the monotonicity for the head of the line processor sharing(HLPS) servers in which the units in the heads of the queues are served simultaneously and the bandwidth allocated to each queue are determined by the numbers of units in the queues. GPS is a type of monotonic HLPS. We obtain the HLPS server whose queue length of a class stochastically bounds upper that of corresponding class in the given monotonic HLPS server for all classes. The queue lengths process of all classes in the obtained HLPS server has the stationary distribution of product form. When the given monotonic HLPS server is GPS server, we obtain the explicit form of the stationary queue lengths distribution of the bounding HLPS server. Numerical result shows how tight the stochastic bound is.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1866-1883
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• 2019

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.29-38
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• 2007

The Korea National Police Agency launched a campaign to encourage drivers in stop line observance and to discourage stop line violation by intensively imposing fines. It was to increase stop line observance of drivers and thus traffic safety. According to statistics, the stop line observance rate was increased over 80 % of drivers during the campaign but regressed to the past after the campaign. This paper delivers the effect of the location of traffic signal lights on driver's stop line observance and develops a guideline to improve highway traffic environment in long terms. Statistical tests conducted based on field data showed that the drivers' stop line observance increases when traffic signal lights are closely installed from a stop line. It was proposed from the study that traffic signal lights be installed $10{\sim}20m$ from a stop line.

• Journal of Environmental Health Sciences
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• v.30 no.3
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• pp.293-299
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• 2004

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristics of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends is towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a model of vehicle emission calculation by using real-time traffic data was studied. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It is possible that characteristics of hourly air pollutants emission rates is obtained from hourly traffic volume and speed. An emission rates model is allocated with a high resolution space by using geographic information system (GIS). Vehicle emission model was developed with a high resolution spatial, gridded and hourly emission rates.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.203-215
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• 2003

In order to provide the drivers with more reliable transportation information in NHTMS(National Highway Transportation Management System), it is important to estimate the expected passage time by using the traffic volume and speed. In this study, we analyze the characteristics of the traffic volume in the national highway and we investigate two real-time adjustment methods: the average adjustment method and the auto-regressive adjustment method. In addition, we compare them using the real data collected at the National Highway Route 3 in 2000.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1881-1903
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• 2015

With the fast-developing of mobile terminals, positioning techniques based on fingerprinting method draws attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve its performance, we propose a radio map building and updating technique, which is able to customize the spatial and temporal dependency of radio maps. The method includes indoor propagation and penetration modeling and the analysis of human traffic. Based on the combination of Ray-Tracing Algorithm, Finite-Different Time-Domain and Rough Set Theory, the approach of indoor propagation modeling accurately represents the spatial dependency of the radio map. In terms of temporal dependency, we specifically study the factor of moving people in the interest area. With measurement and statistics, the factor of human traffic is introduced as the temporal updating component. We improve our existing indoor positioning system with the proposed building and updating method, and compare the localization accuracy. The results show that the enhanced system can conquer the influence caused by moving people, and maintain the confidence probability stable during week, which enhance the actual availability and robustness of fingerprinting-based indoor positioning system.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.835-845
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• 2013

Travel-time is considered the most typical and preferred traffic information for intelligent transportation systems(ITS). This paper proposes a real-time travel-time prediction method for a national highway. In this paper, the K-nearest neighbor(KNN) method is used for travel time prediction. The KNN method (a nonparametric method) is appropriate for a real-time traffic management system because the method needs no additional assumptions or parameter calibration. The performances of various models are compared based on mean absolute percentage error(MAPE) and coefficient of variation(CV). In real application, the analysis of real traffic data collected from Korean national highways indicates that the proposed model outperforms other prediction models such as the historical average model and the Kalman filter model. It is expected to improve travel-time reliability by flexibly using travel-time from the proposed model with travel-time from the interval detectors.