• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.26-36
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• 2020

The use of existing macroscopic research of pedestrian behavior on the walking link as data is limited in determining an individual pedestrian's moving route and the level of service. In macroscopic studies, it is difficult to make quantitative indices, such as pedestrian flow rate, occupied space, density, and speed for determining the level of service on pedestrian roads. Therefore, the microscopic pedestrian route is required to establish appropriate pedestrian policies. In this study, the Yeok-Sam subway station network was examined using a micro-simulation VISSIM, which was then calibrated and validated statistically. The Pedestrian Road's Level of Service of Yeok-Sam subway station area was evaluated using the pedestrian speed as the evaluating index on the Korean highway capacity handbook.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.7-9
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• 2009

Because unlike cars, pedestrians are not moving along the middle axis of street lanes, PNS needs more sophisticated information. So we defined the specific needs of pedestrians, analyzed already existing geodata sets and selected the reasonable layers.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• Journal of IKEEE
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• v.21 no.3
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• pp.244-247
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• 2017

In this paper, we implemented a convolution neural network using GP-GPU. After defining the structure, CNN performed inferencing using the GP-GPU with 256 threads, which was the previous study, using the weight obtained from the training. Training used Intel i7-4470 CPU and Matlab. Dataset used Daimler Pedestrian Dataset. The GP-GPU is controlled by the PC using PCIe and operates as an FPGA. We assigned a thread according to the depth and size of each layer. In the case of the pooling layer, we used over warpping pooling to perform additional operations on the horizontal and vertical regions. One inferencing takes about 12 ms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.840-860
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• 2023

Aiming at the serious occlusion and slow tracking speed in pedestrian target tracking and recognition in complex scenes, a target tracking method based on improved YOLO v5 combined with Deep SORT is proposed. By merging the attention mechanism ECA-Net with the Neck part of the YOLO v5 network, using the CIoU loss function and the method of CIoU non-maximum value suppression, connecting the Deep SORT model using Shuffle Net V2 as the appearance feature extraction network to achieve lightweight and fast speed tracking and the purpose of improving tracking under occlusion. A large number of experiments show that the improved YOLO v5 increases the average precision by 1.3% compared with other algorithms. The improved tracking model, MOTA reaches 54.3% on the MOT17 pedestrian tracking data, and the tracking accuracy is 3.7% higher than the related algorithms and The model presented in this paper improves the FPS by nearly 5 on the fps indicator.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.7-8
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• 2010

Due to development of wireless environment and portable device, it is possible to use navigation out of car. Specially, pedestrians can freely walk openspace, so there are limits that we use network data of car navigation systems for pedestrian navigation systems. Therefore, in this paper, we proposed the method of generating network data for pedestrians based on the exiting spatial data sets.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.11-16
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• 2010

Various researches have been performed on the topic of pedestrian traffic flow. At the beginning, the modeling and simulation method for the vehicular traffic flow was simply applied to pedestrian traffic flow. Recently, CA based simulation models are frequently applied to pedestrian flow analysis. Initially, the square Lattice Model is a base model for applying to pedestrians of counterflow and then Hexagonal Lattice Model improves its network as a hexagonal cell for more realistic movement of the avoidance of pedestrian conflicts. However these lattice models express only one directional movement because they express only one directional movement. In this paper, MLPM (the Multi-Layer Pedestrian Model) is suggested to give various origins and destinations for more realistic pedestrian motion in some place.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.28-32
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• 2020

Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.808-810
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• 2018

Pedestrian tracking is a particular problem of object tracking, and an important component in various vision-based applications, such as autonomous cars or surveillance systems. After several years of development, pedestrian tracking in videos is still a challenging problem because of various visual properties of objects and surrounding environment. In this research, we propose a tracking-by-detection system for pedestrian tracking, which incorporates Convolutional Neural Network (CNN) and color information. Pedestrians in video frames are localized by a CNN, then detected pedestrians are assigned to their corresponding tracklets based on similarities in color distributions. The experimental results show that our system was able to overcome various difficulties to produce highly accurate tracking results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.613-621
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• 2019

In general, transfer in subway stations is defined as transfer between lines and station transfer. In transfer between lines, passengers change from one subway line to another by utilizing horizontal pedestrian facilities such as transfer passages and pedestrian way. Station transfer appears in the situation that subway lines of enter and exit gate terminals differs from those of boarding and alighting trains and passenger trips utilize both vertical pedestrian facilities such as stair and escalator and horizontal facilities. The hypothesis on these two transfers presupposes that all subway lines are operated by either local train or express in subway network. This means that in a transfer case both local and express trains are operated in the same subway line, as a case of Seoul Metro Line 9, has not been studied. This research proposes a methodology of finding the same line transfer in the Seoul metropolitan subway network built based on the smart card network data by suggesting expanded network concept and a model that passengers choose a theirs minimum time routes.