• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.67-79
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• 2002

In this paper, observed trajectories of a vehicle platoon are viewed as one realization of a finite sequence of random trajectories. In this point of view, we develop novel and mathematically rigorous concept of traffic flow variables such as local traffic density, instantaneous traffic flow, and velocity field and investigate their nature on a general probability space of a sequence of random trajectories which represent vehicle trajectories. We present a simple model of random trajectories as an illustrative example and, derive the values of traffic flow variables based on the new definitions in this model. In particular, we construct the model for the sequence of random vehicle trajectories with a system of stochastic differential equations. Each equation of the system nay represent microscopic random maneuvering behavior of each vehicle with properly designed drift coefficient functions and diffusion coefficient functions. The system of stochastic differential equations nay generate a well-defined probability space of a sequence of random vehicle trajectories. We derive the partial differential equation for the expected cumulative plot with appropriate initial conditions. By solving the equation with numerical methods, we obtain the values of expected cumulative plot, local traffic density, and instantaneous traffic flow. In addition, we derive the partial differential equation for the expected travel time to a certain location with appropriate initial and/or boundary conditions, which is solvable numerically. We apply this model to a case of single vehicle trajectory.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.181-188
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• 2015

This paper present, the result of the guidance and control law for a course correction munitions(CCM) with 2sets of canards positioned in the rotating nose section. The nonlinear simulation model of the CCM was developed based on 7DOF equation of motion. The ability of correcting position was verified by open-loop control input with nonlinear model. The guidance and control command was constructed by reference trajectory which can be obtained with no control. Finally, the performance of the guidance and control law was evaluated through Monte-carlo simulation. The CEP(Circular Error Probability) was obtained by considering the errors in muzzle velocity, aerodynamic coefficient, wind, elevation and azimuth angle and density.

• Korean Journal of Computational Design and Engineering
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• v.19 no.4
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• pp.340-346
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• 2014

There are many factors that contribute to hit probability of the gun shot of ground combat vehicles. Aiming accuracy is mainly affected by the dynamic state of the vehicle. The stabilization error of the turret under system vibration is one of the major factors that affect the aiming accuracy. The vibration of the vehicle is affected by both the state of the road and the speed of the vehicle. This paper analyzes the aiming accuracy of the gun equipped on the GCV when the vehicle drives on the different roads and at different speed. The vertical displacement and the pitch angle of the gun are calculated and the impact points of the target are calculated. Distribution of the impact points on the target is greatly influenced by the pitch rotation rather than vertical displacement. And this aiming errors result in the errors of point of impacts on the target after the bullet flies through the air under trajectory equations. The GCV is modeled using a half-car model with 6 D.O.F. and the specifications of the M2 machine gun are used in trajectory calculation simulation and the target is located in 1000 m away from the gun.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.908-928
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• 2022

Multiple target tracking mainly focuses on tracking unknown number of targets in the complex environment of clutter and missed detection. The generalized labeled multi-Bernoulli (GLMB) filter has been shown to be an effective approach and attracted extensive attention. However, in the scenarios where the clutter rate is high or measurement-outliers often occur, the performance of the GLMB filter will significantly decline due to the Gaussian-based likelihood function is sensitive to clutter. To solve this problem, this paper presents a robust GLMB filter and smoother to improve the tracking performance in the scenarios with high clutter rate, low detection probability, and measurement-outliers. Firstly, a Student-T distribution variational Bayesian (TDVB) filtering technology is employed to update targets' states. Then, The likelihood weight in the tracking process is deduced again. Finally, a trajectory smoothing method is proposed to improve the integrative tracking performance. The proposed method are compared with recent multiple target tracking filters, and the simulation results show that the proposed method can effectively improve tracking accuracy in the scenarios with high clutter rate, low detection rate and measurement-outliers. Code is published on GitHub.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.52.2-52.2
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• 2019

In the last decades, the use of type Ia supernovae (SN) as standard candles has allowed us to understand the geometry of the Universe as they help to measure the expansion rate of the Universe, especially in combination with other cosmological probes such as the study of cosmic microwave background radiation anisotropies or the study of the imprint of baryonic acoustic oscillations on the galaxy clustering. Cosmological parameter constraints obtained with type Ia SN are mainly affected by intrinsic systematic errors. But there are other systematic effects related with the correlation of the observed brightness of Supernova and the large-scale structure of the Universe such as the effect of peculiar velocities and gravitational lensing. The former is relevant for SN at low redshifts while the latter starts being relevant for SN at higher redshifts. Gravitational lensing depends on how much matter is along the trajectory of each SN light beam. In order to account for this effect, we consider a statistical approach by defining the probability distribution (PDF) that a given supernova brightness is magnified by a given amount, for a particular redshift. We will show that different theoretical approaches to define the matter density along the light trajectory hugely affect the shape and width of the PDF. This may have catastrophic effects on cosmology fits using Supernova lensing as planned for surveys such as the Dark Energy Survey or future surveys such the Large Synoptic Survey Telescope.

• Journal of KIISE:Software and Applications
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• v.29 no.3
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• pp.167-179
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• 2002

In this paper, we propose a new acoustic model for characterizing segmental features and an algorithm based upon a general framework of hidden Markov models (HMMs) in order to compensate the weakness of HMM assumptions. The segmental features are represented as a trajectory of observed vector sequences by a polynomial regression function because the single frame feature cannot represent the temporal dynamics of speech signals effectively. To apply the segmental features to pattern classification, we adopted segmental HMM(SHMM) which is known as the effective method to represent the trend of speech signals. SHMM separates observation probability of the given state into extra- and intra-segmental variations that show the long-term and short-term variabilities, respectively. To consider the segmental characteristics in acoustic model, we present segmental-feature HMM(SFHMM) by modifying the SHMM. The SFHMM therefore represents the external- and internal-variation as the observation probability of the trajectory in a given state and trajectory estimation error for the given segment, respectively. We conducted several experiments on the TIMIT database to establish the effectiveness of the proposed method and the characteristics of the segmental features. From the experimental results, we conclude that the proposed method is valuable, if its number of parameters is greater than that of conventional HMM, in the flexible and informative feature representation and the performance improvement.

• 한국노년학
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• v.39 no.1
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• pp.37-60
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• 2019

This study was attempt to derive the aging trajectories of Korean elderly people and identify its characteristics. In particular, this study used the successful aging model of Rowe and Kahn as an analytical framework. Using the Korean Longitudinal Study of Ageing(KLoSA), this study applied group-based multi-trajectory analysis to identify multiple aging trajectories in sample of Korean elder aged 65~74(n=2,682). This study also used several demographic characteristics as baseline predictors to identify the characteristics of each aging trajectory. Five dimensions were analyzed in the multi-trajectory model: chronic disease, physical functional limitation, cognitive functioning, depressive symptom and social engagement. As a result of the analysis, five aging trajectories were identified: successful aging(17.8%), usual aging (33.9%), health declining aging(18.2%), pathological aging(7.9%), and aging with mild cognitive impairment(22.1%). In general, the odds of experiencing successful aging were high in men, low-aged, highly educated, high-income, and spousal elderly. On the other hand, for the elderly, who are under-educated, low-income, and high-aged, there was a high probability of experiencing a relatively difficult aging process. In particular, the odds of experiencing a mild cognitive impairment aging was high in older, lower-income women without a spouse.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.57-65
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• 2013

We developed a computer program (CDFlow v. 1.0) to design countermeasures against debris flows in natural terrain. The program can predict the probability of landslides occurring in natural terrain and can estimate the zone of damage caused by a debris flow. It can also be used to design the location and size of countermeasures against the debris flow. The program is run using the ArcGIS Engine, which is one of the most well-known Geographic Information System (GIS) tools for developers. The quasi-dynamic wetness index and the infinite slope stability equation were applied to predict landslide probability as a type of slope safety factor. The calculated safety factor was compared with the required safety factor, and areas of high probable potential for landslides were then selected and represented on the digital map. The volume of debris flow was estimated using these areas of high probable potential for landslides and soil depth. The accumulated volume of debris flow can be calculated along the flow channel. To assess the accuracy of the program, it was applied to a real landslide site at Deoksan-ri, Inje-gun, Kangwon-Province, where four debris barriers have been installed in the watershed of the site. The results of soil tests and a field survey indicate that the program has great potential for estimating probable landslide areas and the trajectory of debris flows. Calculation of the capacity volume of existing debris barriers revealed that they had insufficient capacity to store the calculated amount of debris flow. Therefore, this program enables a rational estimation of the optimal location and size of debris barriers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.63-75
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• 2018

A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.