• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.83-91
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• 2011

The roadmap DB update for unknown roads is a very important factor for car navigation systems. In this paper, we propose a cloud computing based roadmap generation method for use between heterogeneous navigation system for unknown roads. While the drivers drive on unknown roads, the proposed method extracts the road attribute information, and then generates the metadata in an XML format that is available for the heterogeneous navigation systems in a cloud environment. The metadata is proposed to be used as a replacement for conventional proprietary roadmap formats which used by roadmap providers, which is efficient for heterogeneous navigation system providers in a cloud computing environment. Then, this metadata is provided to the roadmap DB providers through the cloud computing interfaces. With the proposed method, the roadmap DB providers update the own roadmap DB for navigation systems in real time. Therefore, the proposed method can reduce the costs of an actual traveling test and the maintenance for the roadmap DB provides. Thus, the cloud-oriented road map generation method can more efficiently update the unknown road information.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.179-187
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• 2011

Multiple roadmap DB providers are already available in these days, and try to reduce unknown roads in their own roadmaps. However, cooperation models or Win-Win approaches between roadmap providers are not considered yet. Thus, In this paper, We proposed a cloud-oriented real-time roadmap generation and update method between heterogeneous navigation systems for unknown roads. With the proposed method, the roadmap DB providers update the own roadmap DB for navigation systems in real time. Also, they can provide the complete roadmap without unknown roads to users instantly. Therefore, the proposed method can reduce the costs of an actual traveling test and the maintenance for the roadmap DB provides. Thus, the cloud-oriented roadmap generation method can more efficiently update the unknown road information.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.403-404
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• 2014

WAVE(Wireless Access in Vehicular Environment)에서 V2V(Vehicle to Vehicle) 통신 시 OBU(On Board Unit)인 자동차 단말은 수신한 정보가 제대로 된 정보인지를 확인하는 과정에서 공인인증서가 필요하다. 동시에 자동차 단말은 이 공인인증서의 상태가 유효한 지를 확인해야 한다. 이것을 확인하는 방법은 자동차 단말이 도로변에 설치돼 있는 RSU(Road Side Unit)인 OCSP(Online Certificate Status Protocol) 서버에게 공인인증서의 상태 확인 요청을 하는 것이다. OCSP 서버는 자동차 단말의 요청에 응답하기 위해서 인증서 폐지 목록인 CRL(Certificate Revocation List)을 가지고 있어야 한다. 본 논문에서는 WAVE 시스템의 OCSP 서버가 공인인증서 상태 정보를 자동차 단말로 알려줄 수 있도록 하기 위해 CA(Certificate Authority)의 CRL 저장소로부터 CRL 을 업데이트 하는 프로토콜을 제안한다. OCSP 서버가 CRL 을 업데이트 할 때, OCSP 서버가 가지고 있는 CRL 과 CRL 저장소가 가지고 있는 CRL 의 값을 비교하여 두 값이 같은 경우에는 CRL 을 업데이트 하지 않도록 한다. OCSP 서버가 선택적으로 CRL 을 업데이트 함으로써 불필요한 부하를 줄일 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.315-316
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• 2009

차량용 네비게이션에 사용되는 지도는 새로운 도로를 추가하거나 폐쇄된 도로를 삭제하는데 어려움을 겪는다. 이는 네비게이션 벤더에 의해 변경된 도로가 업데이트 되기 때문인데 벤더가 변경된 도로를 알아내기 위해서는 실제로 도로를 조사하는 등의 경비가 소모되므로 잦은 업데이트가 어렵다. 이런 문제를 해결하기 위해서 본 논문에서는 블루투스를 이용한 차량간 애드혹 네트워크를 이용해서 실시간으로 주변 도로의 형태를 생성하는 방법을 제안한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.193-202
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• 2021

The update of a high-precision map was carried out by modifying the geometric information using ortho-images or point-cloud data as the source data and then reconstructing the relationship between the spatial objects. These series of processes take considerable time to process the geometric information, making it difficult to apply real-time route planning to a vehicle quickly. Therefore, this study proposed a method to update the road network for route planning using a graph data structure and storage type of graph data structure considering the characteristics of the road network. The proposed method was also reviewed to assess the feasibility of real-time route information transmission by applying it to actual road data.

• Journal of KIISE
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• v.43 no.3
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• pp.389-397
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• 2016

In this paper, we propose a highway safety system that comprises a small number of central servers and smart mobile devices. To implement this system, we constructed a central server that collects GPS location information on cars, whose update messages are decreased via the car location estimation algorithm. The in-car mobile devices use the accelerometer sensors to detect hazardous situations; this information is updated to the central server that relays the information to the corresponding endangered cars via location-based unicast using LTE communication. To evaluate the proposed algorithm, we equipped a mobile device app on a real car and conducted real experiments in various environments such as city streets, rural areas, and highway roads. Furthermore, we conducted simulations to evaluate the propagation of danger information. Finally, we conducted simulated experiments to detect car collisions as well as exceptions, such as falling of the mobile device from the cradle.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.29-34
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• 2008

Demand for car navigation systems has been an explosive increase because of prevalence of owner-drivers, spare time spread, and so on. In addition, car navigation systems are achieving a rapid growth to be the important part of telematics industry with services such as real-time traffic information and DMB(Digital Multimedia Broadcasting). The network data, one of the composition components in car navigation systems, is most important component because that is abstract of real world road network and base data in pathfinding. However most of the car navigation systems have been stand-alone system. Thus user's network data becomes outdated according to the time passing and does not reflect the change of road information in real world. To overcome this problem, users have to update network data in car navigation systems periodically. This method is quite cumbersome process. For this reason, this study proposed a new update method to serve the difference network data on user's device and the real world in real time, and simulated to verify.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.71-80
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• 2012

This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle's location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.66-75
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• 2010

The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.