• Title/Summary/Keyword: Network of Roads

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Forwarding Protocol Along with Angle Priority in Vehicular Networks (차량 통신망에서 Angle 우선순위를 가진 Forwarding 프로토콜)

  • Yu, Suk-Dea;Lee, Dong-Chun
    • Convergence Security Journal
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    • v.10 no.1
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    • pp.41-48
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    • 2010
  • Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.

A Clustering Scheme for Discovering Congested Routes on Road Networks

  • Li, He;Bok, Kyoung Soo;Lim, Jong Tae;Lee, Byoung Yup;Yoo, Jae Soo
    • Journal of Electrical Engineering and Technology
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    • v.10 no.4
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    • pp.1836-1842
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    • 2015
  • On road networks, the clustering of moving objects is important for traffic monitoring and routes recommendation. The existing schemes find out density route by considering the number of vehicles in a road segment. Since they don’t consider the features of each road segment such as width, length, and directions in a road network, the results are not correct in some real road networks. To overcome such problems, we propose a clustering method for congested routes discovering from the trajectories of moving objects on road networks. The proposed scheme can be divided into three steps. First, it divides each road network into segments with different width, length, and directions. Second, the congested road segments are detected through analyzing the trajectories of moving objects on the road network. The saturation degree of each road segment and the average moving speed of vehicles in a road segment are computed to detect the congested road segments. Finally, we compute the final congested routes by using a clustering scheme. The experimental results showed that the proposed scheme can efficiently discover the congested routes in different directions of the roads.

Landslide prediction system by wireless sensor network (무선센서 네트워크를 이용한 산사태 모니터링 기초기술 연구)

  • Kim, Hyung-Woo
    • 한국정보통신설비학회:학술대회논문집
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    • 2007.08a
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    • pp.191-195
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    • 2007
  • Recently, landslides frequently happen at a natural slope during period of intensive rainfall. With rapidly increasing population of steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is developed. The system is focused to debris flows which happen frequently during periods of intensive rainfall at steep slopes in Kangwondo. This system is based on the wireless sensor network that is composed of sensor nodes, gateway, and server system. Sensor nodes that are composed of sensing part and communication part are newly developed to detect sensitive ground movement. Sensing part is designed to measure tilt angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15. I) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of laboratory tests is performed at a small-scale earth slope supplying rainfall by artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope failure starts. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs, and can be applied to ubiquitous computing city (U-City) that is characterized by disaster free.

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Landslide monitoring using wireless sensor network (무선센서 네트워크에 의한 경사면 계측 실용화 연구)

  • Kim, Hyung-Woo
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.03a
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    • pp.1324-1331
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    • 2008
  • Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes and gateway are deployed with Microstrain G-Link system. Five wireless sensor nodes and gateway are installed at the man-made slope to detect landslide. It is found that the acceleration data of each sensor node can be obtained via wireless sensor networks. Additionally, thresholds to determine whether the slope will be stable or not are proposed using finite element analysis. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

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Evaluation of Vehicle and Pedestrian Environments using Grey System Theory (Grey System Theory를 이용한 차량 및 보행환경 통합평가)

  • Lee, Jin-Gak;Son, Yeong-Tae;Han, Sang-Jin;Park, Jin-Yeong;Lee, Sang-Hwa
    • Journal of Korean Society of Transportation
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    • v.28 no.4
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    • pp.141-156
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    • 2010
  • In this paper, understanding there is a limitation with a comprehensive and network approach for the evaluation of existing vehicle and pedestrian environments, the authors focus on developing an integrated approach to assessing these environments. The network evaluation here means the assessment at a three-dimensional level that includes evaluation methods of lines/axes in a spatial concept as well as integration of evaluation indicators being used for vehicles and the walking environment. Grey System Theory (GST) was applied based on the theoretical background for network and comprehensive integrated evaluation, and the evaluation of the vehicle and pedestrian environment was performed by assigning target areas to walking preference zones. As a result of the comprehensive evaluation and analysis by GST, even if the service level is the same as the operating indicators (Highway Capacity Manual) of the vehicle and pedestrian environment, or relatively better, it was identified that the total score could be varied over Grey Category because the observed data are calculated after considering the weights between evaluation indicators by the range of Grey Category on the comprehensive evaluation. Considering comprehensively these points, although the indicators on the operation of roads are relatively good, in the event that the indicators on the safety of roads are bad, it was known that the scores over Grey Category also could be changed. The result is that this evaluation method can be used to evaluate the network concept per lane (per axis) as well as to diagnose the current state by type of urban street in the future.

Development of a Spatial Location-Allocation Model of Center Villages (I) - Development and Verification of Model - (농촌중심마을의 공간적 입지-배분 모형의 개발(I) - 모형의 개발 및 검증 -)

  • 김대식;정하우
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.2
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    • pp.112-121
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    • 2001
  • In this study, a spatial location-allocation model of center villages (SLAMCV) was developed for selecting spatial center villages and allocating their rear villages. In SLAMCV, rural space was considered as a network with villages for nodes and roads for connecting lines. For quantification of residents’ accessibilities in the network, a disutility index (DUI) was developed and used, which is dependent upon travelling distance between the center and its hinter villages, design vehicle speed in connecting road and population of hinter villages. SLAMCV was verified to Christaller’s hexagonal hierachical settlement system to test the theoretical reasonability and computing algorithm of the model.

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Distributed Optimal Path Generation Based on Delayed Routing in Smart Camera Networks

  • Zhang, Yaying;Lu, Wangyan;Sun, Yuanhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3100-3116
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    • 2016
  • With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

Real Time Traffic Signal Plan using Neural Network

  • Choi Myeong-Bok;Hong You-Sik
    • 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.

Intelligent Traffic Light using Fuzzy Neural Network

  • Park, Myeong-Bok;You-Sik, Hong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.66-71
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    • 2003
  • 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. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.

A Study on Development of Visual Navigation System based on Neural Network Learning

  • Shin, Suk-Young;Lee, Jang-Hee;You, Yang-Jun;Kang, Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.1
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    • pp.1-8
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    • 2002
  • It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads without any specific marks such as painted guide line or tape. In this method the robot navigates with visual sensors, which uses visual information to navigate itself along the read. The Neural Network System was used to learn driving pattern and decide where to move. In this paper, I will present a vision-based process for AMR(Autonomous Mobile Robot) that is able to navigate on the indoor read with simple computation. We used a single USB-type web camera to construct smaller and cheaper navigation system instead of expensive CCD camera.