• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.657-659
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• 2000

The importance of total management for maritime structures (Ports, Piers, docks. marine bridges, marine roads, submarine pipelines, etc.) is more and more increasing in these days. Especially, in spite of the marine structures are exposed at the various corrosion circumstances, there are not only a standard of Cathodic Protection System but also knowledge of importance for necessity of corrosion monitoring. Therefore, this paper presents the results of development for the Remote Real-Time Corrosion Monitoring and Control System Using by TRS on Maritime Metallic Structures which can be prevents a big accident by corrosion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.360-366
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• 2005

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, $30-45\%$ of conventional traffic cycle is not matched to the present traffic cycle. In this paper we proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which doesn't consider vehicle length.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.5-10
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• 2013

This paper describes a Forward Collision Warning (FCW) system based on the radar driven fusion with camera. The objective of FCW system is to provide an appropriate alert with satisfying the evaluation scenarios of US-NCAP and a driver acceptance. For this purpose, this paper proposed a data fusion algorithm and a collision warning algorithm. The data fusion algorithm generates information of fusion target depending on the confidence of camera sensor. The collision warning algorithm calculates indexes and determines an appropriate alert-timing by using analysis results of manual driving data. The FCW system with the proposed data fusion and collision warning algorithm was investigated via scenarios of US-NCAP and a real-road driving. It is shown that the proposed FCW system can improve the accuracy of an alarm-timing and reduce the false alarm in real roads.

• Journal of the Korean housing association
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• v.21 no.4
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• pp.89-97
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• 2010

Digital convergence era has been already started and is rapidly developed. Recently, convergency technology became an essential issue in all industries, and is expected to accelerate. This means that we can experience growth and change of architecture using new technology and approaching method. The AR (Augmented Reality) technology, among these convergence technology, is a kind of virtual reality technology that user can see a scene of real world which is overlapped by virtual world with additional information. It has been used in manufacturing and management in the whole industry fields including medical, mechanical, military field and so on because it can provide higher sense of reality. Thus, in this paper, we suggest the utilization of AR technology for organically connecting the roads, facilities, green area, landscape and others in the layout planning of housing complex. Users can see real world with virtual object by overlap computer graphic on the real world. This method provides users with various information about territoriality and openness. As the result of this study it is expected that this technology will help the layout planning of housing complex to become more reasonable in the aspect of design, time and cost.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.9-14
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• 2002

The durability prediction of emission control components, especially 02 sensor and catalytic converter, is getting more important as emission regulation is getting stricter and vehicle durability mileage requirement is also extended from 80,000 ㎞ to 160,000 km in Korean market. And the duration of vehicle mileage accumulation to get vehicle exhaust emission deterioration factor for certification is required to be shorter in order to reduce the vehicle development time. Since most of the vehicle emission development tests are done on chassis dynamometer and aging bench by using vehicle aging modes, real road condition and in-use driving patterns must be reflected into them to predict the vehicle emission level and to meet emission regulation especially at high mileage. In order to get the frequent driving pattern of vehicle and the aging characteristic of emission components, a vehicle was tested by changing drivers and driving roads around Seoul. Real road driving patterns were analyzed and compared with those of the certification modes which are well known in automotive industry.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.191-206
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• 2018

In this study, the HAPs(Harzard Air Pollutants) emission factor level of Starex and Grand Carnival was tested using PEMS (Portable Emissions Measurement System) on real road driving. As a result of RDE (Real Driving Emission test), the overall vehicle speed pattern showed similar characteristics. The real-road driving test at constant speed revealed emission factor is inversely proportional relationship to constant speed. Results of accelerating with speed limit on the real-road were shown as followings; Uran (less than 45 km/h)>Rural (<45 km/h, less than 80 km/h)>Motorway (>80 km/h). Moreover, the sudden acceleration and deceleration in driving at high speed was the increasing factor to the HAPs emission factor. This tendency is considered to be influenced by the operating environment on real roads.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.405-422
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• 2014

Two important issues in hedonic model are to specify accurate model and delineate submarkets. While the former has experienced much improvement over recent decades, the latter has received relatively little attention. However, the accuracy of estimates from hedonic model will be necessarily reduced when the analysis does not adequately address market segmentation which can capture the spatial scale of price formation process in real estate. Placing emphasis on improvement of performance in hedonic model, this paper tried to segment real estate markets in Gangnam-gu and Jungrang-gu, which correspond to most heterogeneous and homogeneous ones respectively in 25 autonomous districts of Seoul. First, we calculated variable coefficients from mixed geographically weighted regression model (mixed GWR model) as input for clustering, since the coefficient from hedonic model can be interpreted as shadow price of attributes constituting real estate. After that, we developed a spatially constrained data-driven methodology to preserve spatial contiguity by utilizing the SKATER algorithm based on a minimum spanning tree. Finally, the performance of this method was verified by applying a multi-level model. We concluded that submarket does not exist in Jungrang-gu and five submarkets centered on arterial roads would be reasonable in Gangnam-gu. Urban infrastructure such as arterial roads has not been considered an important factor for delineating submarkets until now, but it was found empirically that they play a key role in market segmentation.