• Title/Summary/Keyword: 차선 예측

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Risk Factors for Pediatric Inpatient Falls (아동 입원환자의 낙상위험 예측요인)

  • Cho, Myung Sook;Song, Mi Ra;Cha, Sun Kyung
    • Journal of Korean Academy of Nursing
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    • v.43 no.5
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    • pp.595-604
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    • 2013
  • Purpose: The purpose of this study was to identify risk factors for pediatric inpatients falls. Methods: The study was a matched case-control design. The participants were 279 patients under the age of 6 who were admitted between January 1, 2004 and December 31, 2009. Through chart reviews, 93 pediatric patients who fell and 186 ones who did not fall were paired by gender, age, diagnosis, and length of stay. Five experts evaluated the 38 fall risk factors selected by the researchers. Results: In a general hospital, pediatric patients with secondary diagnosis, tests that need the patient to be moved, intravenous lines, hyperactivity, anxiolytics, sedatives and hypnotics, and general anesthetics showed significance for falls on adjusted-odds ratios. Conditional logistic regression analysis was performed to elucidate the factors that influence pediatric inpatient falls. The probability of falls increased with hyperactivity and general weakness. Patients who didn't have tests that required them to be moved and intravenous line had a higher risk of falls. Conclusion: These findings provide information that is relevant in developing fall risk assessment tools and prevention programs for pediatric inpatient falls.

Vehicle Stabilization Using MPC Based on Nonlinear Tire Model (비선형 타이어모델 기반 MPC를 이용한 차량 안정화)

  • Song, Yuho;Kim, Hansu;Kim, Seungki;Kim, Youngwoo;Lee, Tae Hee;Huh, Kunsoo
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.6
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    • pp.730-736
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    • 2016
  • Recent research suggests the various applications of Model Predictive Control on vehicle systems. In numerous cases, nonlinear tire models such as the Magic Formula, which are highly complex and are more detailed than necessary, are used. This paper presents a nonlinear tire model that excludes the region of negative slope but expresses the nonlinear properties of tire well enough for tracking the lane of a racing course. The proposed inverse tire model can also be used to calculate the slip angle from the tire force. Thus, the model can be utilized to design the Model Predictive Controller.

Car-following Motion Planning for Autonomous Vehicles in Multi-lane Environments (자율주행 차량의 다 차선 환경 내 차량 추종 경로 계획)

  • Seo, Changpil;Yi, Kyoungsu
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.3
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    • pp.30-36
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    • 2019
  • This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

A Study on the Predictive Model of Propagation Path Loss in Millimeter-Wave Band (밀리미터파 대역에서 전파경로손실 예측 모델)

  • Kim, Song-Min
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.42 no.2
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    • pp.23-28
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    • 2005
  • This study was to suggest the propagation path loss and predictive model of propagation path analysis in order to apply the frequency in the millimeter-wave band to the real time inter-vehicle communication system. This study was to suppose the case of inter-vehicle communication on the one-way two-lanes road in the big cites with a lot of traffic jams in order to analyze the effect by the reflected wave of multipath. As a simulation of suggested model, it found out that the propagation path by the reflected wave was about 0.1[m]$\sim$5.1[m] longer than the one by the direct wave during the transmission of 100[m] wave direct path. Also, as a result of comparing the propagation path loss, the loss would be about -0.8[dB]$\sim$-4.2[dB] larger in case of wall reflection and -0.8[dB]$\sim$-1[dB] vehicle reflection. From the result above, this researcher found out that the path loss of reflected wave produced by the walls was about -3.2[dB] larger than the path loss produced by the adjacent vehicles.

A Study on the Implementation of Microscopic Traffic Simulation Model by Using GIS (GIS를 이용한 미시적 수준의 교통모형 구현에 관한 연구)

  • Kim, Byeongsun
    • Spatial Information Research
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    • v.23 no.4
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    • pp.79-89
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    • 2015
  • This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

The Estimation of the Regional Gross Capital Stock in Transport Sector of Korea (교통부문의 지역별 자본스톡 추정)

  • 하헌구;조희덕
    • Journal of Korean Society of Transportation
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    • v.20 no.6
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    • pp.45-56
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    • 2002
  • In this research we estimated regional gross fixed capital stock of transport sector, such as road railroad, airport and seaport during 1968-1997 in Korea. We also compared our estimation results with those of Korea and Japan. As basic analytic method, we used the regional allocation method. To estimate regional gross fixed capital stock of transport sector, we used the basic data on national wealth surveys in 1997, regional land price index and regional facilities index in transport sectors. We used the most reasonable data in the process of estimation after reviewing the collected data In order to get the reasonable capital stock by regions. we chose the allocation index which can minimize the difference between the estimated result and the real regional capital stock in the process to allocate the total gross capital into the regions. Compared our results with those of other researches in Korea, estimates in our research project could be said more accurate than those.

Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System (정밀도로지도 제작을 위한 모바일매핑시스템 기반 딥러닝 학습데이터의 자동 구축)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.133-139
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    • 2021
  • Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

Predictive Algorithm of Self-Control System using Load Control Model applied to Automobile Dynamic (하중모델을 이용한 자동차 운동 분석과 자율 예측 시스템 알고리즘)

  • Wang, Hyun-Min;Woo, Kwang-Joon
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.4
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    • pp.61-68
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    • 2010
  • Appling high technology of aerospace to automobile, so it is able to progress safety which is a goal of future automobile and to approach development of self-control automobile. This is realized dynamic model of airplane at DFCS(Digital Flight Control System). The DFCS calculates control values for self-control flight. If this high technology applies to automobile, then it is able to be maneuvered automobile like UAV's self-control flight. In this paper is reanalyzed automobile dynamic applied load control model used high-tech of airplane. It analyzes riding comfortable according to movement of automobile using the load control model, presents method of solution for improvement riding comfortable and presents example of self-control system used the load control model for self-control driving.

Real-Time Lane Detection Based on Inverse Perspective Transform and Search Range Prediction (역원근 변환과 검색 영역 예측에 의한 실시간 차선 인식)

  • Kim, S.H.;Lee, D.H.;Lee, M.H.;Be, J.I.
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2843-2845
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    • 2000
  • A lane detection based on a road model or feature all need correct acquirement of information on the lane in a image, It is inefficient to implement a lane detection algorithm through the full range of a image when being applied to a real road in real time because of the calculating time. This paper defines two searching range of detecting lane in a road, First is searching mode that is searching the lane without any prior information of a road, Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It is allow to extract accurately and efficiently the edge candidates points of a lane as not conducting an unnecessary searching. By means of removing the perspective effect of the edge candidate points which are acquired by using the inverse perspective transformation, we transform the edge candidate information in the Image Coordinate System(ICS) into the plane-view image in the World Coordinate System(WCS). We define linear approximation filter and remove the fault edge candidate points by using it This paper aims to approximate more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.

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Complete genome sequences of Azoarcus sp. TSPY31 and TSNA42 potentially having biosynthetic ability to produce indigo (인디고 생산능을 가진 Azoarcus sp. TSPY31과 TSNA42의 유전체 분석)

  • Kim, Hae-Seon;Cha, Sun Ho;Suk, Ho Young;Park, Nyun-Ho;Woo, Jung-Hee
    • Korean Journal of Microbiology
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    • v.54 no.3
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    • pp.283-285
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    • 2018
  • Azoarcus are known to contain bacterial strains usually found in contaminated areas. Two strains of Azoarcus sp., TSPY31 and TSNA42, were isolated from oil-contaminated marine tidal flats, and their genomic structures were analyzed. The genomes of both TSPY31 and TSNA42 were composed of a single complete chromosome of 4,572,082 bp (G + C content: 63.2%) and 4,886,934 bp (G + C content: 62.8%), respectively. Both genomes were found to contain two copies of styrene monooxygenases that are predicted to be responsible for converting indole to indigo.