• Title/Summary/Keyword: road-based

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A Network-based Indexing Method for Trajectories of Moving Objects on Roads (도로 위에 존재하는 이동객체의 궤적에 대한 네트워크 기반의 색인 방법)

  • Kim, Kyoung-Sook;Li, Ki-Joune
    • The KIPS Transactions:PartD
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    • v.13D no.7 s.110
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    • pp.879-888
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    • 2006
  • Recently many researchers have focused on management of Historical trajectories of moving objects in Euclidean spaces due to numerous sizes of accumulated data over time. However, the movement of moving objects in real applications generally has some constraints, for example vehicles on roads can only travel along connected road networks. In this paper, we propose an indexing method for trajectories of moving objects on road networks in order to process the network-based spatiotemporal range query. Our method contains the connect information of road networks to use the network distance for query processing, deals with trajectories which are represented by road segments in road networks, and manages them using multiple R-trees assigned per each road segment. Furthermore, it has a structure to be able to share R-tree among several road segments in large road networks. Consequently, we show that our method takes about 30% less in node accesses for the network-based spatiotemporal range query processing than other methods based on the Euclidean distance by experiments.

Effective Road Area Extraction in Satellite Images Using Texture-Based BP Neural Network (텍스쳐 기반 BP 신경망을 이용한 위성영상의 도로영역 추출)

  • Xu, Zheng;Kim, Bo-Ram;Oh, Jun-Taek;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.10 no.3
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    • pp.164-169
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    • 2009
  • This paper proposes a road detection method using BP(Back-Propagation) neural network based on texture information of the each candidate road region segmented for satellite images. To segment the candidate road regions, the histogram-based binarization method proposed by N.Otsu is firstly performed and the neighboring regions surrounding road regions are then removed. And after extracting the principal color using the histogram of the segmented foreground, the candidate road regions are classified into the regions within ${\pm}25$ of the principal color. Finally, the road regions are segmented using BP neural network based on texture information of the candidate regions. The texture information in this paper is calculated using co-occurrence matrix and is used as an input data of the BP neural network. The proposed method is based on the fact that the road has the constant intensity and shape. The experiment demonstrated the validity of the proposed method and showed 90% detection accuracy for the various images.

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Road Slide Detection Algorithm Using CCD Camera (CCD 카메라를 이용한 도로 붕괴 사태 검출 알고리즘)

  • Kwon, Young-Man;Shin, Se-Yeon;Park, Young-Jin;Kim, Eun-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.181-187
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    • 2011
  • In this paper, we proposed the vision-based efficient algorithm for road slide detection like as destruction of road cut slope. The proposed algorithm defines the image region as non surveillance and surveillance which is further divided by road, boundary and non road region. After that, it find the moving block, remember the history of movement using the TTL(Time To Live) table, determine the road slide by checking the existence of moving blocks from non road region to road region together. We confirmed the proposed algorithm detected the road slide effectively through experiments.

An Estimation Method of Drivable Path for Unmanned Ground Vehicle Using Camera and 2D Laser Rangefinder on Unpaved Road (카메라와 2차원 레이저 거리센서를 활용한 비포장 도로 환경에서의 지상무인차량의 주행가능영역 추정 기법)

  • Ahn, Seong-Yong;Kim, Chong-Hui;Choe, Tok-Son;Park, Yong-Woon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.6
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    • pp.993-1001
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    • 2011
  • Unmanned ground vehicle for facility protection mostly uses model of territory for autonomous navigation. However, modeling of territory using several sensors is highly time consuming and sometimes inefficient for road application. Therefore, an estimation of drivable path based on features of road is required for high speed autonomous navigation on road. In this paper, an estimation method of drivable path using camera and 2D laser rangefinder is proposed. First, a vanishing point is estimated based on image data from CCD camera. Second, a road width is estimated based on range data from 2D laser rangefinder. Finally, the drivable path is estimated by fusing the vanishing point and the road width. The proposed method is tested on both well-structured road and unpaved road like cross-country situation.

States/Road Input Observer-based Control of Semi-active Suspensions (상태변수/노면입력 관측기를 이용한 반능동 현가시스템 제어)

  • 김정헌;이경수
    • Transactions of the Korean Society of Automotive Engineers
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    • v.8 no.2
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    • pp.102-109
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    • 2000
  • This paper deals with an observer-based preview control for semi-active suspensions. An Observer has been designed such that all the state variables and road inputs can be estimated from accelerations. Since the road input to the rear wheels is a delayed version of that to the front wheels, it can be obtained by estimating the road input to the front wheels without preview the estimated values of state and the estimated road input has been investigated. The results show that the observer-based control can provide good performance. The observer-based preview control improves the dynamic behavior of the rear axle and that of pitch motion compared to the LQ optimal control.

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A Study on Factors that Influence Traffic Accident Severity in Road Surface Freezing (결빙구간의 교통사고 심각도 영향 요인 연구)

  • Lee, Sang Jun
    • Journal of the Korean Society of Safety
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    • v.32 no.6
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    • pp.150-156
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    • 2017
  • A frozen road surface increases traffic accidents during the winter season. Hence, information on easily-frozen road sections and their specificities are required to prevent traffic accidents. Frozen road surfaces are determined by equipment measuring road surface temperatures. However, there are limitations in investigating the entire road network. Therefore, it is imperative to develop new methods that effectively determine road surface freezing risks. Meteorologically, road surfaces are frozen when the actual temperature cools down to the dew point temperature. Under this condition, there is likely to be frost if relative humidity reaches 100% and frozen road surfaces as the temperature gets lower. Meteorological characteristics give us an alternative to a direct measurement road surface temperature to estimate risks of road surface freezing. Based on the clues, the relationship between severity of traffic accidents and temperature changes is empirically investigated using Paju weather data. The results reveal that as the temperature gets lower and changes in current temperature are relatively small, the severity of traffic accidents become higher. In addition, the same is true when the difference between current temperature and the dew point temperature is relatively small, as it increases possibilities of road surface freezing. Future studies must investigate how current temperature and the dew point temperature affect road surface freezing and thereby establish a time-space scope to estimate possible road surface freezing sections using only weather and road material type data. This would provide invaluable information for predicting and preventing frozen road accidents based on weather patterns.

Decision of Road Direction by Polygonal Approximation. (다각근사법을 이용한 도로방향 결정)

  • Lim, Young-Cheol;Park, Jong-Gun;Kim, Eui-Sun;Park, Jin-Su;Park, Chang-Seok
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1398-1400
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    • 1996
  • In this paper, a method of the decision of the road direction for ALV(Autonomous Land Vehicle) road following by region-based segmentation is presented. The decision of the road direction requires extracting road regions from images in real-time to guide the navigation of ALV on the roadway. Two thresholds to discriminate between road and non-road region in the image are easily decided, using knowledge of problem region and polygonal approximation that searches multiple peaks and valleys in histogram of a road image. The most likely road region of the binary image is selected from original image by these steps. The location of a vanishing point to indicate the direction of the road can be obtained applying it to X-Y profile of the binary road region again. It can successfully steer a ALV along a road reliably, even in the presence of fluctuation of illumination condition, bad road surface condition such as hidden boundaries, shadows, road patches, dirt and water stains, and unusual road condition. Pyramid structure also saves time in processing road images and a real-time image processing for achieving navigation of ALV is implemented. The efficacy of this approach is demonstrated using several real-world road images.

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Impact of Spatial Accessibility Index, Based on Road Network and Actual Trips, on Housing Price (도로 네트워크와 통행량 기반의 공간 접근성 지수가 주택가격에 미치는 영향)

  • Chae, Jung Pyo;Sung, Hyungun
    • Journal of Korea Planning Association
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    • v.54 no.2
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    • pp.76-83
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    • 2019
  • This study aims to empirically identify the effect of spatial accessibility, based on travel, on housing prices in the Korean capital region. More specifically, it has two research purposes: First, investigating the effect of comprehensive spatial accessibility, based on road network and actual trips from origin to destination, on average apartment price (Korean Won per square meter) at the level of Eup, Myeon and Dong; Second, identifying better accessibility index between Hansen's and Kalogirou and Foley's ones. The former represents a road-based travel time decay function with destination trips, while the latter is a function with origin trips as well as destination ones. The study employs spatial economic models considering spatial auto-correlative relationship as an appropriate methodology with such control independent indicators as population density, road density, educational environment and distances from CBDs. Analysis results demonstrate that spatial accessibility, based on road network and actual trips from origin to destination, has a statistically significant impacts on housing price in the region. Our empirical evidence proves that the Hansen index is more appropriate than the other in estimating housing price impacts.

The Development of Ubiquitous Road Disaster Management System (유비쿼터스 도로재해관리시스템 개발연구)

  • Sung, Dong-Gwan;Choi, Young-Taek;Ko, Jae-Woong;Cho, Gi-Sung
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.301-306
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    • 2007
  • Because the cost of road management is increasing proportional to road construction, there are needs to build general and systematic road management system. To solving such problems, Ministry of Construction and Transportation started research and development of Highway Management System(HMS), and established a foundation for systematic road management system. But, the implementation of HMS has some limitations because it is just converting roads of physical space to roads of electronic space and managing roads of electronic space. Although HMS offers many conveniences compared to old system which was based hard-copy and paper maps or unit operations, it can not overcome the problem of inefficency of road management due to the separation of operation between outer field and inner office. Therefore, to overcome such inefficency, this study focused on Road Disaster Management System development based on Ubiquotous.

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Local Path Plan for Unpaved Road in Rough Environment (야지환경의 비포장도로용 지역경로계획)

  • Lee, Young-Il;Choe, Tok Son;Park, Yong Woon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.6
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    • pp.726-732
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    • 2013
  • It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.