• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.87-104
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• 2015

Currently the IoT (Internet of Things) environments and related technologies are being developed rapidly through the networks for connecting many intelligent objects. The IoT is providing artificial intelligent services combined with context recognition based knowledge and communication methods between human and objects and objects to objects. With the help of IoT technology, many research works are being developed using the C-ITS (Cooperative Intelligent Transport System) which uses road infrastructure and traveling vehicles as traffic control infrastructures and resources for improving and increasing driver's convenience and safety through two way communication such as bus-only lane and license plate recognition and road accidents, works ahead reports, which are eventually for advancing traffic effectiveness. In this paper, a system for deciding whether the traveling vehicle is possible or not to drive on bus-only lane in highway is researched using the lane and number plate recognition on the road in C-ITS traffic infrastructure environments. The number plates of vehicles on the straight ahead and sides are identified after the location of bus-only lane is discovered through the lane recognition method. Research results and experimental outcomes are presented which are supposed to be used by traffic management infrastructure and controlling system in future.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.2
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• pp.45-56
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• 2013

The precise identification of vehicle positions, known as the vehicle localization problem, is an important requirement for building intelligent vehicle ad-hoc networks (VANETs). To solve this problem, two categories of solutions are proposed: stand-alone and data fusion approaches. Compared to stand-alone approaches, which use single information including the global positioning system (GPS) and sensor-based navigation systems with differential corrections, data fusion approaches analyze the position information of several vehicles from GPS and sensor-based navigation systems, etc. Therefore, data fusion approaches show high accuracy. With the position information on a set of vehicles in the preprocessing stage, data fusion approaches is used to estimate the precise vehicular location in the local map building stage. This paper proposes an efficient local map building scheme, which increases the accuracy of the estimated vehicle positions via V2V communications. Even under the low ratio of vehicles with communication modules on the road, the proposed local map building scheme showed high accuracy when estimating the vehicle positions. From the experimental results based on the parameters of the practical vehicular environments, the accuracy of the proposed localization system approached the single lane-level.

• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.45-59
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• 1996

The shortest path algorithm for route guidance is implicitly required not only to support geometrical variations of transportation network such as U-TURN or P-TURN but to efficiency search reasonable routes in searching mechanism. The purpose of this paper is to integrate such two requirements ; that is, to allow U-TURN and P-TURN possibilities and to cut down searching time in locating routes between two points (origin and destination) in networks. We also propose a new type of link searching algorithm which can solve the limitation of vine building algorithm at consecutively left-turn prohibited intersections. The test site is a block of Gangnam road network that has some left-turn prohibited and allowed U-TURN intersections. Four models have been identified to be comparatively analyzed in terms of searching efficiency. The Models are as follows : (i) Model 1 - Link Searching Dijkstra Algorithm without Searching Area Extraction (SAE) ; (ii) Model 2 - Link Searching Dijkstra Algorithm with SAE ; (iii) Model 3 - Link Searching Bidirectional Dijkstra Algorithm without SAE ; and (iv) Model 4 - Link Searching Bidirectional Dijkstra Algorithm with SAE. The results of comparative evaluation show that Model 4 can effectively find optimum path faster than any other models as expected. Some discussions and future research agenda have been presented in the light of dynamic route guidance application of the urban ATIS.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.224-229
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• 2004

The objective of this work is not only to perform feasibility studies on the CFD (computational fluid dynamics) analysis for the capillary system design but also to provide an enhanced understanding of the autonomous capillary flow. The capillary flow is evaluated by means of the commercial CFD software of FLUENT, which includes the VOF (volume-of-fluid) model for multiphase flow analysis. The effect of wall adhesion at fluid interfaces in contact with rigid boundaries is considered in terms of static contact angle. Feasibility studies are first performed, including mesh-resolution influence on pressure profile, which has a sudden increase at the liquid/gas interface. Then we perform both 2D and 3D simulations and examine the transient nature of the capillary flow. Analytical solutions are also derived for simple cases and compared with numerical results. Through this work, essential information on the capillary system design is brought out. Our efforts and initial success in numerical description of the microfluidic capillary flows enhance the fundamental understanding of the autonomous capillary flow and will eventually pave the road for full-scale, computer-aided design of microfluidic networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2619-2625
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• 2011

The GPS technique widely used recently in car navigation system has two problems that are unavailability in urban canyons and inherent positional error rate. The one has been studied and solved in many literatures. However, the other still leads to incorrect locational information in some area, especially parallel roads. This paper proposes and implements a system to recognize lane of moving vehicle based on images obtained from in-vehicle networks or other devices. The proposed system utilizes a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. It also employs a method for accuracy improvement. The results obtained from experimental test on real-time navigation show that the proposed systems works well and the accuracy increases.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.26-32
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• 2011

Recently, in the U-health area, there are research related on monitoring brainwaves in real-time for coping with emergent situations like the fatigue driving, cerebral infarction or the heart attack of not only the patients but also the normal elderly folks by transmitting of the EEG(Electroencephalograph). This system could be applied to hospitals or sanatoriums. In this paper, it is applied for the vehicular ad-hoc network to prevent the car accident in advance by monitoring the brainwaves of a driver in real-time. In order to do this, I used mobile ad-hoc nodes supported in the Opnet simulator for the efficient EEG brainwave transmission in the VANET environment. The vehicular ad-hoc networks transmitting the brainwaves to the nearest road-side unit are designed and simulated to draw an efficient and proper vehicular ad-hoc network environment.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.121-131
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• 2014

PURPOSES : The goal of this study is to analyze the travel cost according to transferring from rotary to roundabout in Korea. METHODS : This study gives particular attentions to investigating the existing 48 rotaries in Korea and building the networks of before and after improvements using VISSIM, and analyzing their travel costs. RESULTS : The main results are as follows. First, from the field survey, the domestic rotaries were analyzed to need many improvements of geometric structure for the effective operation. Second, the difference of travel cost at 3-legged rotaries were evaluated to be less than other types of rotaries due to low traffic volume. Finally, the travel cost of 4-legged and multi-legged rotaries were analyzed to rapidly increase by increasing volume. CONCLUSIONS : This study analyzes the effects using both real and simulation data unlike the existing studies. Also, this study suggests the future research topics which compare and evaluate the relations between real data and simulation outputs.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.99-108
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• 2001

A framework of using and integrating GIS and OR tools for determining the best site selection has been provided. In this research, we demonstrated that both the P-Median heuristic method and MIP method can be successfully applied to the optimum site selection problem of oil tank location selection. Furthermore, the results identified by both approaches are identical. To accomplish this, both GIS road and maritime networks have been constructed and combined to calculated the minimum distance matrix, which is required by both approaches. After the application to the Korean peninsula, the facility locations chosen are Kunsan, Yosu, Busan, and Okgye for each district. As has been shown, the power of GIS and both algorithm have been demonstrated throughout the research and further similar research can also be conducted using the power of GIS and Operations Research tools.