• Journal of the Society of Disaster Information
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• v.15 no.1
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• pp.76-83
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• 2019

Purpose: The purpose of this study is to present data of density and speed through the experiment of the counterflow by firefighter in corridor. Method: Experimental setup including a corridor in building was prepared for measuring data with 1.5m and 2m width. Normal flow and counterflow were created for each. Data were measured using camera and acquired by video image analysis. Results: The counterflow in corridor resulted in increasing average density of about $0.55P/m^2$ and decreasing average movement speed of about 0.61 m/s. These data measured during the time when the counterflow occurred. Conclusion: It was found that counterflow by firefighter in corridor momentary increasing the density and decreasing walking speed of evacuee. Further experiments of the counterflow effect in the total evacuation time are needed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.56-67
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• 2018

In general, fire and evacuation simulators are used independently to diagnose the safety of building. Because this method does not reflect the movement of pedestrians considering fire spread, it is difficult to expect diagnosis of safety with high accuracy. In this study, we propose the simulation method that can describe the movement of pedestrians in the fire emergency. Our method reflects the FDS fire spread data into FFM and explains the situation in which a pedestrian recognize a fire and escapes to a safe route. This study consists of data linkage between FDS and FFM and development of improved FFM. Experiment of the proposed method is progressed using the EgresSIM. Simulation result shows that the number of evacuees on each exit is affected by the presence or absence of fire and it was confirmed that the evacuation time increase and the bottleneck phenomenon deepened by exit.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.117-123
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• 2023

There are casualties due to inundation and flooding due to intensive typhoons or heavy rains in summer. Due to such damage, the biggest disaster is flood, and in order to reduce human damage, this paper proposes a shortest distance algorithm-based pedestrian path search study using Map API. This system selects Map API through comparative analysis and provides the shortest route. The route explored is in JSON format and the data of the shelter is stored in the database. The route search system designed and implemented based on this data locates pedestrians and provides evacuation routes in case of flash floods. In addition, if the route cannot be entered while moving to the evacuation route, the current location of the pedestrian is identified, the route is re-searched, and a new route is provided. Therefore, it is believed that the pedestrian route search system proposed in this paper will prevent negligent accidents.

• Transportation Technology and Policy
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• v.13 no.1
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• pp.15-22
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• 2016

• Transportation Technology and Policy
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• v.13 no.5
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• pp.29-36
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• 2016

• Journal of KIISE
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• v.44 no.1
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• pp.44-50
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• 2017

Pedestrian detection, an important component of autonomous driving and driving assistant system, has been extensively studied for many years. In particular, image based pedestrian detection methods such as Hierarchical classifier or HOG and, deep models such as ConvNet are well studied. The evaluation score has increased by the various methods. However, pedestrian detection requires high sensitivity to errors, since small error can lead to life or death problems. Consequently, further reduction in pedestrian detection error rate of autonomous systems is required. We proposed a new method to detect pedestrians and reduce the error rate by using the Faster R-CNN with new developed pedestrian training data sets. Finally, we compared the proposed method with the previous models, in order to show the improvement of our method.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.421-429
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• 2015

This paper is about an approach for pedestrian detection and tracking with infrared imagery. We used the CUDA(Computer Unified Device Architecture) that is a parallel processing language in order to improve the speed of video-based pedestrian detection and tracking. The detection phase is performed by Adaboost algorithm based on Haar-like features. Adaboost classifier is trained with datasets generated from infrared images. After detecting the pedestrian with the Adaboost classifier, we proposed a particle filter tracking strategies on HSV histogram feature that exploit adaptively at the same time. The proposed approach is implemented on an NVIDIA Jetson TK1 developer board that is full-featured device ideal for software development within the Linux environment. In this paper, we presented the results of parallel processing with the NVIDIA GPU on the CUDA development environment for detection and tracking of pedestrians. We compared the object detection and tracking processing time for night-time images on both GPU and CPU. The result showed that the detection and tracking speed of the pedestrian with GPU is approximately 6 times faster than that for CPU.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.119-127
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• 2014

TIn this paper, Hemiplegic patients have gait characteristics different from normal persons. This paper presents a posture measuring and display system reflecting their characteristics. Patients wear 3 sensor modules on thigh, calf and foot. To enhance measuring precision of each sensor module, 3D accelerometer and 3D gyroscope are combined. Gait posture is displayed in 3D by modeling thigh, calf and foot as connected 3D objects based on data of the sensor modules. For convenience in inspecting unusual gait posture of hemiplegic patients, any view angle of the 3D display can be selected. In addition, the current gait phase of RLA(Rancho Los Amigos) gait cycle is determined and displayed in real-time by utilizing the posture information, The phase sequence and duration of each phase can be used in evaluating gait quality of patients.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.4
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• pp.191-197
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• 2005

Biped walking is the main feature of a humanoid robot. In a biped walking robot, there are many actuators to be controlled and many sensors to be interfaced. In this paper, we propose a DSP-based controller for a miniature biped walking robot with 21 RC servo motors. The proposed controller has a hierarchical structure; a host PC, a DSP-based main controller, and an auxiliary controller with an FPGA chip. The host PC generates and transmits the robot walking data for given walking parameters such as stride, walking period, etc. The main controller implemented with a TMS320LF2407A controls 21 RC servo motors via the auxiliary controller. We also perform some experiments for balancing motion and walking on a slope terrain with interfacing a 2-axis acceleration sensor and a TMS320LF2407A.