• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1201-1210
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• 2007

The urban streets as a featured and well performing public space for people should be organized in a way that can work as a whole system through network as well as that can provide amenities fur pedestrian. This is a study on Seattle's 'Blue Ring' project for an analysis focused on how its street weaving system organized and what are the design characteristics of the streets. The results are as followings. (1)Pedestrian oriented design, (2)Urban street as a part of open space that can accommodate human activities, (3)Integrated, not isolated with outer/ other open space, (4)Organically networked in a hierarchical manner that can promote pedestrian movement, (5)Utilization of regionally identical design elements. And Smart Growth concept lies in the core of 'Blue Ring' project.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.271-280
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• 2023

Pedestrian Dead Reckoning (PDR) methods using initial sensors are being studied to provide the location information of smart device users in indoor environments where satellite signals are not available. PDR can continuously estimate the location of a pedestrian regardless of the walking environment, but has the disadvantage of accumulating errors over time. Unlike this, WiFi signal-based wireless positioning technology does not accumulate errors over time, but can provide positioning information only where infrastructure is installed. It also shows different positioning performance depending on the environment. In this paper, an integrated positioning technology integrating two positioning techniques with different error characteristics is proposed. A technique for correcting the error of PDR was designed by using the location information obtained through WiFi Measurement-based fingerprinting as the measurement of Extended Kalman Filte (EKF). Here, a technique is used to variably calculate the error covariance of the filter measurements using the WiFi Fingerprinting DB and apply it to the filter. The performance of the proposed positioning technology is verified through an experiment. The error characteristics of the PDR and WiFi Fingerprinting techniques are analyzed through the experimental results. In addition, it is confirmed that the PDR error is effectively compensated by adaptively utilizing the WiFi signal to the environment through the EKF to which the adaptive error covariance proposed in this paper is applied.

• Transportation Technology and Policy
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• v.13 no.2
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• pp.74-82
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• 2016

• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Journal of Auto-vehicle Safety Association
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• v.4 no.2
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• pp.32-36
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• 2012

The Automatic unmanned target object carrying system (AUTOCS) is developed for testing road vehicle radar and vision sensor. It is important for the target to reflect the realistic target characteristics when developing ASV or ADAS products. The AUTOCS is developed to move the pedestrian or motorcycle target for desired speed and position. The AUTOCS is designed that only payload target which is a manikin or a motorcycle is detected by the sensor not the AUTOCS itself. In order for the AUTOCS to have low exposure to radar, the AUTOCS is stealthy shaped to have low RCS(Radar Cross Section). For deceiving vision sensor, the AUTOCS has a specially designed pattern on outside skin which resembles the asphalt pattern. The AUTOCS has three driving modes which are remote control, path following and replay. The AUTOCS V.1 is tested to verify the radar detect characteristics, and the AUTOCS successfully demonstrated that it is not detected by a car radar. The result is presented in this paper.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.396-408
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• 2017

In Korea, the number of elderly has been increasing rapidly. So it is also expected that the economic activity and the trip frequency of the elderly will increase. On the other hand, elderly related accidents such as falls during walking are steadily increasing and the satisfaction about pedestrian environment of elderly is very low. In this paper, we found one of the reasons for these dissatisfaction in pedestrian facility, which is not considering the walking ability (about 75% of non-elderly person) of the elderly. So, we analyze the kinematic walking characteristics of the elderly with the motion analysis system, when the elderly use stairs. As a result of analysis of various walking variables, the current standard for stairway height in Korean law (18cm) requires excessive force to elderly so it was difficult for elderly to keep the balance of the body in ascending and descending walk of stairs. In this paper, we propose the stair design criteria through the cluster analysis of walking parameters reflecting the gait characteristics of the elderly. This change is not a big for non-elderly person, but it can promote more socioeconomic activities for the elderly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.18-35
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• 2020

Many human, roadway, and vehicle factors affect vehicle-pedestrian crashes. Especially, the roadway factors are easily defined and suitable for suggesting countermeasures. The characteristics of the road network are one of the roadway factors. The road network significantly influences behaviors and conflicts of drivers and pedestrians. A metropolitan city such as Seoul contains various types of road networks, and crash prevention strategy considering characteristics of the road network is required. In this study, we analyze the effects of road networks on vehicle-pedestrian crashes. In the study, high order road ratio, intersection ratio, high-low intersection ratio are considered as road network variables. Using Geographically Weighted Poisson Regression, crash frequencies in Dongs of Seoul are analyzed based on the road network variable as well as socioeconomic variables. As a result, Dongs are grouped by coefficient signs, and each group is suggested about improvement directions considering conflict situations.