• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.1-11
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• 2015

This paper is focused on how the trajectory of launch vehicle could be optimally estimated by the quadratic regression of trajectory data mining for the operation of telemetry ground system in NARO space center during real-time. To receive the telemetry data, the telemetry ground system has to track the space launch vehicle without tracking loss, and it is possible by the well-designed algorithm to estimate a flight position in real-time. For this reason, the quadratic regression model instead of interpolation was considered to estimate the exact position data of launch vehicle and the improvement of antenna performance. For analysis, the real trajectory data which had been logged during NARO 1st launch mission were used, the estimation result of launcher current position was analyzed by the mathematical modeling. In conclusion, the algorithm using quadratic regression based on trajectory data mining showed the better performance than previous interpolation algorithm to estimate the next flight position and the antenna driving performance.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.173-181
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• 2013

In this paper, the design result of the trajectory-based air traffic analysis software which is going to be used to assess air-traffic efficiency in case that some modification's made in dynamic airspace configuration, is described. The software has been developed to make statistical data about air-traffic in Incheon FIR based on the RPL, and to analyze the airway utilization and controller workload using the trajectory modeling data which are derived from the aircraft type, cruise speed, cruise altitude, and routes and fixes in the RPL. Since it batch-processes the long-term trajectory data with other inputs such as airspace, route information and so on, it has the advantage of quickly predicting the traffic variation when some change in airspace and route information is made.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.53-61
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• 2014

For monitoring the flight trajectory and the status of a launch vehicle, the mission control system in NARO space center process data acquired from the ground tracking system, which consists of two tracking radars, four telemetry stations, and one electro-optical tracking system. Each tracking unit exhibits its own tracking error mainly due to multi-path, clutter and radio refraction, and by utilizing only one among transmitted informations, it is not possible to determine the actual vehicle trajectory. This paper presents a way of generating flight trajectory via post-processing the data received from the ground tracking system. The post-processing algorithm is divided into two parts: compensation for atmosphere radio refraction and multi-sensor fusion, for which a decentralized Kalman filter was adopted and implemented based on constant acceleration model. Applications of the present scheme to real data resulted in the flight trajectory where the tracking errors were minimized than done by any one sensor.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.13-24
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• 2014

Satellite remote sensing data have been valuable tool for volcanic ash monitoring. In this study, we present the results of application of satellite remote sensing data for monitoring of volcanic ash for three major volcanic eruption cases (2008 Chait$\acute{e}$n, 2010 Eyjafjallaj$\ddot{o}$kull, and 2011 Shinmoedake volcanoes). Volcanic ash detection products based on the Moderate Resolution Imaging Spectro-radiometer (MODIS) observation data using infrared brightness temperature difference technique were compared to the forward air mass trajectory analysis by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. There was good correlation between MODIS volcanic ash image and trajectory lines after the volcanic eruptions, which support the feasibility of using the integration of satellite observed and model derived data for volcanic ash forecasting.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.175-181
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• 2009

Intelligent Transportation Systems(ITS) enables road users to enhance efficiency of their trips in a variety of traffic conditions. As a significant part of ITS, information communication technology among vehicles and between vehicles and infrastructure has been being developed to upgrade current traffic data collection technology through location-based traffic surveillance systems. A wider and detailed range of traffic data can be acquired with ease by the technology. However, its performance level falls with environmental impediments such as large vehicles, buildings, harsh weather, which often bring about wireless communication failure. For imputation of vehicle trajectory data discontinued by the failure, several potential existing methods were reviewed and a new method to complement them was devised. AIMSUN API(Application Programming Interface) software was utilized to simulate vehicle trajectories data and missing vehicle trajectories data was randomly generated for the verification of the method. The method was proven to yield more accurate and reliable traffic data than the existing ones.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.655-666
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• 2021

Purpose: This study is to develop a method for measuring dynamic speeding risks using vehicle trajectory big data and to demonstrate the feasibility of the devised speeding index. Method: The speed behaviors of vehicles were analysed in microscopic space and time using individual vehicle trajectories, and then the boundary condition of speeding (i.e., boundary speed) was determined from the standpoint of crash risk. A novel index for measuring the risk exposure of speeding was developed in microscopic space and time with the boundary speed. Result: A validation study was conducted with vehicle-GPS trajectory big data and ground-truth vehicle crash data. As a result of the analysis, it turned out that the index of speeding-risk exposure has a strong explanatory power (R²=0.7) for motorway traffic accidents. This directly indicates that speeding behaviors should be analysed at a microscopic spatiotemporal dimension. Conclusion: The spatial and temporal evolution of vehicle velocity is very variable. It is, hence, expected that the method presented in this study could be efficaciously employed to analyse the causal factors of traffic accidents and the crash risk exposure in microscopic space using mobility trajectory data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.1-15
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• 2017

Recently terrorism targets unspecified masses and causes massive destruction, which is so-called Super Terrorism. Many countries have tried hard to protect their citizens with various preparation and safety net. With inexpensive and advanced technologies of sensors, the surveillance systems have been paid attention, but few studies associated with the classification of the pedestrians' trajectories and the difference among themselves have attempted. Therefore, we collected individual trajectories at Samseoung Station using an analytical solution (system) of pedestrian trajectory by LiDAR sensor. Based on the collected trajectory data, a comprehensive framework of classifying the types of pedestrians' trajectories has been developed with data normalization and "trajectory association rule-based algorithm." As a result, trajectories with low similarity within the very same cluster is possibly detected.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.326-327
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• 2002

제주도 고산은 지역자체내의 대기오염물질이 거의 없는 우리나라의 대표적인 배경농도지역이며, 지리적 특성상 동북아시아에서 대기오염물질의 장거리이동 특성을 규명하는데 적합한 지역으로 알려져 있다. 고산에 대한 활발한 연구를 통해 장기간 TSP 측정자료가 모아졌으나, 아직까지 그 해석에 대한 통계적인 분석과 이동특성에 관한 해석을 위한 역궤적 분석은 미흡하다. 이에 본 발표에서는 1992년 3월부터 2002년 2월까지 고산에서 측정한 입자상 무기이온 성분의 농도를 장기간의 역궤적 분석결과와 함께 통계적인 방법으로 해석하고자 하였다. (중략)

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.12-31
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• 1999

Topex/Poseidon satellite altimetric data are used to estimate characteristics on the oceanic and atmospheric correction factors, and the mean sea level and its variations in the Yellow Sea, the East China Sea and the East Sea from September 1992 through August 1994(70cycles). For the atmospheric correction factors, the variations of dry troposphere, humid troposphere, ionosphere and inverted barometer were very small as a few centimeters, but the variations of electromagnetic bias were higher than other factors. For the oceanic correction factors, the variations of ocean tide(35cm in track 127 and 60cm in track 214) showed high ranges compared to elastic tide(5cm in track 127 and 1cm in track 214) and loading tide(1.8cm in track 127 and 1cm in track 214). It should be understood that the variations of ocean free surface is mainly under the influence of, firstly, ocean tide and, secondly, electromagnetic bias. Mean sea level in the Yellow Sea are higher than in the rest of Seas. Then its range generally comprised between -60cm and 210cm with mean value of about 100cm. Also its variations showed high values in the Yellow Sea and East China Sea, especially 5.689cm in Youngampo. This result is mainly due to the effects of local topography and tidal current.