• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.1946-1958
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• 2011

Wireless Sensor Network (WSN) is made up of a number of sensor nodes and base stations. Traffic flow in WSN appears self-similar due to its data delivery process, and this impacts queue length greatly and makes queuing delay worse. Active queue management can be designed to improve QoS performance for WSN. In this paper, we propose self-similar traffic rate estimating algorithm named Power-Law Moving Averaging (PLMA) to regulate packet marking probability. This algorithm improves the availability of the rate estimation algorithm under the self-similar traffic condition. Then, we propose an adaptive Proportional Integral algorithm (SSPI) based on the estimation of the Self-Similar traffic rate by PLMA. Simulation results show that SSPI can achieve lower queue length jitter and smaller setting time than PI.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1373-1380
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• 2014

In order to calculate accurate traffic and traffic speed, qualified and sufficient GPS data should be provided. However, it is difficult to provide accurate traffic information using restricted GPS data from probe vehicles because of communication costs. This paper developed a algorithm that recovers links omitted by restricted GPS data with topology information, and calculate traffic speed with original links and recovered links. T traffic information service of city with a new algorithm can provide more accurate traffic and traffic speed than the original system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1375-1378
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• 1997

In this paper, we presents the algorithm which is to recognize the traffic sign on the road the traffic signal in a video image for autonomous navigation. First, the rocognition of traffic sign on the road can be detected using boundary point estimation form some scan-lines within the lane deducted. For this algorithm, index matrix method is used to detemine what sign is. Then, the traffic signal recognition is performed by usign the window minified by several scan-lines which position may be expected. For this algoritm, line profile concept is adopted.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.68-82
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• 2011

Wireless mesh networks (WMNs) provide high-speed backbone networks without any wired cable. Many researchers have tried to increase network throughput by using multi-channel and multi-radio interfaces. A multi-radio multi-channel WMN requires channel assignment algorithm to decide the number of channels needed for each link. Since the channel assignment affects routing and interference directly, it is a critical component for enhancing network performance. However, the optimal channel assignment is known as a NP complete problem. For high performance, most of previous works assign channels in a centralized manner but they are limited in being applied for dynamic network environments. In this paper, we propose a simple flow estimation algorithm and a hybrid channel assignment algorithm. Our flow estimation algorithm obtains aggregated flow rate information between routers by packet sampling, thereby achieving high scalability. Our hybrid channel assignment algorithm initially assigns channels in a centralized manner first, and runs in a distributed manner to adjust channel assignment when notable traffic changes are detected. This approach provides high scalability and high performance compared with existing algorithms, and they are confirmed through extensive performance evaluations.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• 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.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.127-131
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• 2011

Even if there are no causing factors such as car crash and road works, traffic congestion come from traffic growth on the road. In this case, estimation of traffic flow helps find the solution of traffic congestion problem. In this paper, we present a optimization model which used on traffic equilibrium problem and studied the problem of inverting shortest path sets for complex traffic system. And we also develop pivotal decomposition algorithm for reliability function of complex traffic system. Several examples are illustrated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.2 s.7
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• pp.13-22
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• 2005

The purpose of this research is how to estimate the traffic queue length in the signal intersection accurately. The current traffic queue length algorithm in COSMOS has been using the congestion diagram which comes from the speed of an average separated vehicle - using average vehicle length and the occupancy time from loop detectors. So some errors were occurred by the speed estimation method using average vehicle lengths. And Operators had been difficult to optimize some variables for measuring the traffic queue length estimation algorithm in COSMOS. Therefore the traffic queue length estimation algorithm on the basis of the relation between distances and occupancy rates from loop detectors was developed in this thesis. This thesis had the advantage of using occupancy rates which came out from loop detectors easily and no need to optimize some variables for the established algorithm in COSMOS. And the results of testing this algorithm in some sites which had installed COSMOS system showed better results than COSMOS system's results. But it was noted that further studies which carry it out in various sites and under various cases are necessary for applying to actual intersections.