• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.19-27
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• 2021

In this paper, we present a method for effectively predicting traffic volume based on vehicle location data that are collected by using LDP (Local Differential Privacy). The proposed solution in this paper consists of two phases: the process of collecting vehicle location data in a privacy-presering manner and the process of predicting traffic volume using the collected location data. In the first phase, the vehicle's location data is collected by using LDP to prevent privacy issues that may arise during the data collection process. LDP adds random noise to the original data when collecting data to prevent the data owner's sensitive information from being exposed to the outside. This allows the collection of vehicle location data, while preserving the driver's privacy. In the second phase, the traffic volume is predicted by applying deep learning techniques to the data collected in the first stage. Experimental results with real data sets demonstrate that the method proposed in this paper can effectively predict the traffic volume using the location data that are collected in a privacy-preserving manner.

• IE interfaces
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• v.12 no.4
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• pp.625-634
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• 1999

On this study we selected some variable which affect on the estimated of the voice traffic, and estimated daily average traffic by years according to the variables. We applied nonlinear growth curve model to future traffic forecast with estimated historical traffic data. As a result of the forecasting, this study investigates the year in which the internet traffic goes far than the voice traffic.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.11-19
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• 2012

PURPOSES: The new methodology is proposed for estimation of long-term performance and pavement life based on the national highway database in Daejeon area. Furthermore, this study tried to verify the applicability of performance estimation using NHPCI (National Highway Pavement Condition Index) on tendency of pavement deterioration as time goes by under Korean road environments. METHODS: Reliability theories are applied to estimate the mean life and to determine the appropriate distribution using 3 levels of traffic loads (high, medium, low) based on maintenance and rehabilitation history data for 15 years. RESULTS: As a result, Lognormal distribution is suitable for explanation of pavement lifetime in Daejeon area regardless of traffic loads. In addition, we found that the results of mean life and maintenance timing based on NHPCI for the pavement sections of 3 levels of traffic loads are available. CONCLUSIONS: Based on this study, it was found that mean life of high, medium and low levels of traffic loads are about 8.1 years, 12.2 years and 12.7 years, respectively. Higher level of traffic loads shorten the pavement mean life.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.161-167
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• 2008

This paper describes the overview of spectrum requirement estimation recommended in ITU-R Rec. M.1390 and [IMT.METH] and its difference for the IMT mobile service, and a (IMT.METH) methodology is applied to the spectrum estimation of the recent IMT service. The traffic model and traffic calculation algorithm is briefly described for the carried traffic which is determined in terms of the offered traffic, system rapacity, and the criteria of quality of service. And the spectrum requirement demand which is required from year 2010 to year 2015 is calculated as an example for the IMT service which is recently operated and deployed in the current Korean market after obtaining the reasonable market data and the ITU market prediction data.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.97-116
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• 1999

The growing demand for the real time traffic information is bringing about the category and number of traffic collection mechanism in the era of ITS. There are, however, two problems in making data into information using various traffic data. First, the information making process of making data into the representative information, for each traffic collection mechanism, for the specified analysis periods is required. Second, the integration process of fusing each representative information into "the information" for each link out of each source is also required. That is, both data reduction and/or data to information process and information fusion are required. This article is focusing on the development of information fusing algorithm based on voting technique, fuzzy regression, and, Bayesian pooling technique for estimating the dynamic link travel time of networks. The proposed algorithm has been validated using the field experiment data out of GPS probes and detectors over the roadways and the estimated link travel time from the algorithm is proved to be more useful than the mere arithmetic mean from each traffic source.

• International Journal of Highway Engineering
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• v.18 no.5
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• pp.117-125
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• 2016

PURPOSES : The density in uninterrupted traffic flow facilities plays an important role in representing the current status of traffic flow. For example, the density is used for the primary measures of effectiveness in the capacity analysis for freeway facilities. Therefore, the estimation of density has been a long and tough task for traffic engineers for a long time. This study was initiated to evaluate the performance of density values that were estimated using VDS data and two traditional methods, including a method using traffic flow theory and another method using occupancy by comparing the density values estimated using vehicular trajectory data generated from a radar detector. METHODS : In this study, a radar detector which can generate very accurate vehicular trajectory within the range of 250 m on the Joongbu expressway near to Dongseoul tollgate, where two VDS were already installed. The first task was to estimate densities using different data and methods. Thus, the density values were estimated using two traditional methods and the VDS data on the Joongbu expressway. The density values were compared with those estimated using the vehicular trajectory data in order to evaluate the quality of density estimation. Then, the relationship between the space mean speed and density were drawn using two sets of densities and speeds based on the VDS data and one set of those using the radar detector data. CONCLUSIONS : As a result, the three sets of density showed minor differences when the density values were under 20 vehicles per km per lane. However, as the density values become greater than 20 vehicles per km per lane, the three methods showed a significant difference among on another. The density using the vehicular trajectory data showed the lowest values in general. Based on the in-depth study, it was found out that the space mean speed plays a critical role in the calculation of density. The speed estimated from the VDS data was higher than that from the radar detector. In order to validate the difference in the speed data, the traffic flow models using the relationships between the space mean speed and the density were carefully examined in this study. Conclusively, the traffic flow models generated using the radar data seems to be more realistic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.639-645
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• 2007

In this study, an estimation of call demand for the internet telephony was carried out using the monthly time-series data from June 2001 to December 2004. In the estimation, the call traffic was assumed to be explained by tariff of the internet telephony service, tariff of fixed and wireless services, income, quality of service, and lagged traffic variable. The traffic is assumed to follow the partial adjustment mechanism. The estimation result shows that the call traffic demand is elastic to the tariff of the service while it is inelastic to the change of income. The qualisty of service is regarded as an important factor of demand. Also there appeared the call demand is adjusting to the change of explanatory variables with some lags.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.137-147
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• 2005

This study is to define new road capacity concept, and to develop and propose an estimation method, through the analysis of individual vehicular behaviors in continuum flow. Developments in detection technology enable various and precise traffic data collection. The U.S. HCM (Highway Capacity Manual) method does not require such various and precise traffic data, and outputs only limited results. Alternative capacity concepts, which can be classified into a stochastic model and behavioral or deterministic model, are attempts for modeling some prominent traffic flow features, namely so-called a capacity drop and a traffic hysteresis, using such various and precise traffic data. Yet, no capacity concept up-to-date can describe both features. The analysis of individual vehicular behaviors, including speed-density plot per time lap, traffic flow-speed-density diagram per each sampling interval, time headway distribution, and free flow speed distribution, is performed for overcoming the limits of the previous capacity concepts. A stochastic methods are applied to determine time headway for estimating freeway capacity for traffic control.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.795-804
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• 2003

In this article, a tomography for the estimation of the origin-destination(OD) traffic intensities in dynamic routing network is considered. Vardi(1996)'s approach based on fixed route is not directly applicable to dynamic routing protocols, which arises from the fact that we cannot access the route at every observation time. While it uses link-wise traffics as the observations, the proposed method considers the triple of ingress/outgress/relayed traffics data at each node so that we can transform the problem into a routing-independent tomography. An EM algorithm for implementation and some simulated experiments are provided.