• Korean Management Science Review
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• v.23 no.2
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• pp.161-174
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• 2006

In this paper, we consider a network optimization problem arising from the deployment of BcN access network. BcN convergence services requires that access networks satisfy QoS meausres. BcN services have two types of traffics : stream traffic and elastic traffic. Stream traffic uses blocking probability as a QoS measure, while elastic traffic uses delay factor as a QoS measure. Incorporating the QoS requirements, we formulate the problem as a nonlinear mixed-integer Programming model. The Proposed model seeks to find a minimum cost dimensioning solution, while satisfying the QoS requirement. We propose two local search heuristic algorithms for solving the problem, and develop a network design system that implements the developed heuristic algorithms. We demonstrate the computational efficacy of the proposed algorithm by solving a realistic network design problem.

• Journal of Oriental Neuropsychiatry
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• v.19 no.2
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• pp.299-312
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• 2008

Headache is symptom of many people suffered. It caused simply by fatigue, stress, but it also caused by inflammation, mechanical or chemical stimulus, circulation disorder, brain damage. Modern societies develop rapidly by traffic system. But lately it suffering with many traffic problem. Traffic accident is most important of many traffic problem. We experienced a 35 year-old female who complained headache, caused by a traffic accident that happened 22 month ago. We treated the patient by the way of Eo-hyeol (瘀血) type of headache with Herbal medication and Acupuncture. After being treated, the patient show that symptoms(headache, insomnia, anorexia) was improved considerably. This result suggests that oriental medicine treatment has good effect on headache due to traffic accident.

• Journal of the Korean Society of Systems Engineering
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• v.3 no.1
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• pp.27-31
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• 2007

A complex system like ATM(Air Traffic Management) has safety problem emerging from complex interactions between systems. In complex systems, malfunctions of components are not the only causes of critical accidents. To resolve this problem many researchers have proposed new safety analysis models for complex systems. This research is a way of improving safety analysis model focusing on systems engineering design model for ATM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5990-6008
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• 2019

Recognizing license plate from its traffic camera captured images is one of the most important aspects in many traffic management systems. Despite many sophisticated license plate recognition related algorithms available online, license plate recognition is still a hot research issue because license plates in each country all round the world lack of uniform format and their camera captured images are often affected by multiple adverse factors, such as low resolution, poor illumination effects, installation problem etc. A novel method is proposed in this paper to solve the inclination problem of license plates in their camera captured images through four parts: Firstly, special edge pixels of license plate are chosen to represent main information of license plates. Secondly, least square methods are used to compute the inclined angle of license plates. Then, coordinate rotation methods are used to rotate the license plate. At last, bilinear interpolation methods are used to improve the performance of license plate rotation. Several experimental results demonstrated that our proposed method can solve the inclination problem about license plate in visual aspect and can improve the recognition rate when used as the image preprocessing method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.253-263
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• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• IE interfaces
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• v.22 no.4
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• pp.359-367
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• 2009

The vehicle travel time between the demand points in downtown area is greatly influenced by complex road condition and traffic situation that change real time to various external environments. Most of research in the vehicle routing problems compose vehicle routes only considering travel distance and average vehicle speed between the demand points, however did not consider dynamic external environments such as traffic situation by service time zones. A realistic vehicle routing problem which considers traffic situation of smooth, delaying, and stagnating by three service time zones such as going to work, afternoon, and going home was suggested in this study. A mathematical programming model was suggested and it gives an optimal solution when using ILOG CPLEX. A hybrid genetic algorithm was also suggested to chooses a vehicle route considering traffic situation to minimize the total travel time. By comparing the result considering the traffic situation, the suggested algorithm gives better solution than existing algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.722-723
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• 2017

In this study, we take into account in improving traffic flow in real-time problem. In order to solve the problem, we propose a new approach to manage traffic flow at the intersection in real-time via controlling by traffic light scheduling. In particular, the proposed method is based on process synchronization theory and connected vehicle technology where each vehicle is able to communicate with others. The traffic deadlock is also taken into consideration in case of high traffic volume. The simulation shows the potential results comparing with the existing traffic management system.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.257-263
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• 2021

Though many have studied choosing one of the alternative ways to reach a destination, the factors such as average road speed, distance, and number of traffic signals, traffic congestion, safety, and services still presents an indisputable challenge. This paper proposes two approaches: Appropriate membership function and ambiguous rule-based approach. It aims to tackle the route choice problem faced by almost all drivers in any city. It indirectly helps in tackling the problem of traffic congestion. The proposed approach considers the preference of each driver which is determined in a flexible way like a human and stored in the driver profile. These preferences relate to the criteria for evaluating each candidate route, considering the average speed, distance, safety, and services available. An illustrative case study demonstrates the added value of the proposed approach compared to some other approaches.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.99-113
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• 2002

The multi-class traffic assignment problem is the most typical one of the multi-solution traffic assignment problems and, recently formulation of the models and the solution algorithm have been received a great deal of attention. The useful solution algorithm, however, has not been proposed while formulation of the multi-class traffic assignment could be performed by adopting the variational inequality problem or the fixed point problem. In this research, we developed a hybrid solution algorithm which combines GA algorithm, diagonal algorithm and clustering algorithm for the multi-class traffic assignment formulated as a variational inequality Problem. GA algorithm and clustering algorithm are introduced for the wide area and small cost. We also performed an experiment with toy network(2 link) and tested the characteristics of the suggested algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.