• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.187-194
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• 2011

IEEE 802.11 wireless LAN has become the center of attention for one of the most dominant wireless networking technologies nowadays. In densely deployed wireless LANs, mobile stations are exposed to a number of AP, thus it is needed to select the best AP to associate with. The most common approach is to select the AP with the highest received signal strength. However it does not consider traffic load imposed to each AP so that it may cause the poor network performance. Therefore, in this paper, we propose a throughput estimation scheme for neighboring APs by sniffing the traffic within 802.11 networks. We devise a tool, named "VirtFrame", which is to estimate the station's capable throughput from neighbor APs based on the channel access time by virtually combining the sniffed frames. Simulation results show that our proposed scheme well matches that there exists correlation between the channel access time and the actual throughput of the APs.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.39-52
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• 2002

Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.71-79
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• 2005

Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.19-31
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• 2007

When estimating the benefits from an investment project in the transportation sector, errors caused by many factors may exist. This study focuses on user equilibrium traffic assignment methods and stopping criteria. According to previous studies, when using a user equilibrium assignment model, the benefits of travel time savings can be effected by the relative gap value. As the stopping criteria decreases, the time needed for traffic assignment increases, so that lowering the criteria cannot be the best solution. Therefore, an effort is necessary to reduce this change rate and thus improve reliability. This paper considers three methods: reducing the links subject to benefit calculation, extracting sub-area O/D tables and networks, and applying the mean value of successive traffic assignment results. The results of the analysis show that the method using the mean value of five results is more proper than the other methods. Using the sub-area analysis method, if the study area is small the benefits of a project might be over- or under-estimated. This paper used a nationwide O/D table and network at peak time as a case study. The resulting patterns can differ according to basic data to be used in analysis. So further analysis using the data from metropolitan areas are needed.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.306-313
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• 2021

National fishing harbour is as a refuge for fishing boats and a breakwater lighthouse is installed as a functional facility in consideration of harbour identification and the safety of passing vessels. In this study, the service level of breakwater lighthouse (234 units) was estimated based on the traffic volume of 105 national fishing harbour. For this purpose, the evaluation items were determined, the fishing harbour standard index was calculated (Fs=1), the proximity of fishing harbour was identified and the function (service level) of the breakwater lighthouse was estimated in the following order. However, national fishing harbour differed in size, traffic volume and fishing vessel capacity. Therefore, 105 national fishing harbour were divided into three groups through cluster analysis. The cluster analysis was based on the service level factors of the breakwater lighthouse, such as the number of weeding fishing vessels, tonnage of fishing vessels, the number of incoming and outgoing vessels per year, and fishing vessel capacity. As a result of the estimation, the service level of the breakwater lighthouse (light tower height, visual height, visual range, interval) was 10.50m, 16.50m, 7.00mile, 5.5sec for group 1, and 10.67m, 16.16m, 8.33mile, and 6.0sec for group 2, The three groups are 11.53m, 16.75m, 6.75mile and 5.0sec. The results of this study can be used as useful basic data for improving the service level of traffic vessels when a breakwater lighthouse is built in a fishing harbour in the future.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.107-118
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• 2003

Highway Capacity Manual (HCM) provides an analytical delay estimation model to assist the evaluation of traffic at a signalized intersection. The model revised and included in the HCM published in the year 2000 reflects the results of recent studies and is utilized in various fields of transportation studies. For the implementation of the model in the case of permitted left turns, the HCM supplement provides a computational procedure to adjust the saturation flow rate of permitted left toms. The model however, is originally designed for a protected movement and thus underestimates the delay of permitted left turns due to its difference right-of-way nature. This document describes (1) a review of the theoretical background of the HCM delay estimation model, (2) problems embedded in the model for the delay estimation of permitted left turns, (3) a proposed model developed in this study to improve the delay estimation for permitted left turns and (4) a set of verification tests. In order to reflect various traffic and control conditions in the test, simulation studies were performed to by using the field data based on 120 different permitted left-turn scenarios. Comparison studies conducted between sets of delays estimated by the HCM and the proposed models against a set of the CORSIM delays and showed that the proposed model improved the estimation of the permitted left-turn delays. The explanatory variable of the relationship between the HCM delay and the simulation delay was 0.47 and the one between the delay estimated by the proposed model and the simulation delay was 0.77.

• Journal of Korean Society of Transportation
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• v.22 no.1 s.72
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• pp.43-62
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• 2004

Conventionally the estimation method of the origin-destination Matrix has been developed by implementing the expansion of sampled data obtained from roadside interview and household travel survey. In the survey process, the bigger the sample size is, the higher the level of limitation, due to taking time for an error test for a cost and a time. Estimating the O-D matrix from observed traffic count data has been applied as methods of over-coming this limitation, and a gradient model is known as one of the most popular techniques. However, in case of the gradient model, although it may be capable of minimizing the error between the observed and estimated traffic volumes, a prior O-D matrix structure cannot maintained exactly. That is to say, unwanted changes may be occurred. For this reason, this study adopts a conjugate gradient algorithm to take into account two factors: estimation of the O-D matrix from the conjugate gradient algorithm while reflecting the prior O-D matrix structure maintained. This development of the O-D matrix estimation model is to minimize the error between observed and estimated traffic volumes. This study validates the model using the simple network, and then applies it to a large scale network. There are several findings through the tests. First, as the consequence of consistency, it is apparent that the upper level of this model plays a key role by the internal relationship with lower level. Secondly, as the respect of estimation precision, the estimation error is lied within the tolerance interval. Furthermore, the structure of the estimated O-D matrix has not changed too much, and even still has conserved some attributes.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.496-499
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• 2008

The noise reducing devices installed on the noise barrier have been developed in many shapes and ways to reduce noise around road traffic areas. In this study, test and estimation method for the noise reducing device witch installed on the top of a noise barrier was suggested. For this, the authors have considered sound power flow around the device and sound pressure levels for the far field area. To estimate the area effect behind the barrier, area average of noise pressure level difference divided by two area, upper and bellow the sight-line. Comparing the attenuation difference of these areas, the tendency of noise reduction effect was studied according to type of noise reducing devices. Compared with noise shielding efficiency of the devices that using equivalent height of a simple barrier calculated by the SoundPlan, the commercial environment noise simulation software.