• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.2
• /
• pp.246-250
• /
• 2006

The objective of this research was to investigate the way information is used by pedestrians in underground space. Furthermore, we wanted to know how pedestrians utilize information from signage of signs by pedestrians. Thus, we conducted an investigation on the pedestrians' walking behavior in Fukuoka City, Tenjin underground shopping centers, and 1) checked routes taken by the subjects; and 2) categorized the signs that were observed, the pedestrians' movement patterns, the way information from signage isused by the pedestrians, the signs' locations, the relationship between the spaces, the heights of the signs and the types of signs offering directions. The results showed that there is a need to solve certain problems related to the locations of the signs and the walking behaviors of the subjects. To solve the problems exhibited by the subjects' walking behaviors, we came up with a variety of guidance information that could be used. The contents of the guidance information differ depending on the specified heights for the placement of signs and the information used depending on the location. The results also showed that the continuity between places needs to be shown more effectively by the guidance system, and that too many signs are positioned in places where the frequency of use is low.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.1
• /
• pp.31-41
• /
• 2018

This study aims to analyze region-based pedestrian evacuation behaviors and information offering effect using Social Force Model, which is micro simulation. All pedestrians were assumed to move to shelters through pedestrian roads according to guidance information at emergency situations, and the pedestrians were classified into adults and the handicapped. According to the results of the road network analysis and simulation analysis, the shelters to which pedestrians can move within the shortest time from each zone were selected as optimum shelters. From this study, the analysis showed that the information provision effects are informative even though total evacuation time increases due to the increase of pedestrian conflict. This study can be used as baseline data for urban area's pedestrian disaster prevention plans.

• Spatial Information Research
• /
• v.18 no.5
• /
• pp.133-142
• /
• 2010

Many pedestrian or fire evacuation models have been studied last decades for modeling evacuation behaviors or analysing building structures under emergency situations. However, currently developed models do not consider the differences of visibility of pedestrians by obstacles such as furniture, wall, etc. The visibility of pedestrians is considered one of the important factors that affect the evacuation behavior, leading to making simulation results more realistic. In order to incorporate pedestrian's visibility into evacuation simulation, we should be able to give different walking speeds according to differences of visibility. We improved the existing floor field model based on cellular automata in order to implement the visibility. Using the space syntax theory, we showed how we split the indoor spaces depending on the different visibilities created by different levels of structural depths. Then, we improved the algorithm such that pedestrians have different speeds instead of simultaneous movement to other cells. Also, in order for developing a real time simulation system integrated w ith indoor sensors later, we present a process to build a 3D simulator using a spatial DBMS. The proposed algorithm is tested using a campus building.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.10
• /
• pp.162-170
• /
• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of Digital Contents Society
• /
• v.8 no.3
• /
• pp.263-267
• /
• 2007

From our analysis of pedestrian walking behavior at the Daegeon underground shopping center, we think that the following changes might be necessary to improve sign placement and use. First, the discrepancy between the location of information signs and their rate of use should be reduced. Second, differences in information given by the signs that arise from problems with sign height and placement should be reduced. Third, signs should be distributed in such a way that they provide co-ordinated information about points and places. Fourth, the arrangement and placement of the signs should be considered from the view point of pedestrian walking behavior. Because there is difference in the number of installed signs and the rate of use of these signs, to increase the rate of information use it may be necessary to adjust the content and placement of the signs. Furthermore, analysis of subject walking paths shows that it is necessary for information to be offered about connections between spaces.

• Journal of Software Assessment and Valuation
• /
• v.17 no.2
• /
• pp.83-89
• /
• 2021

In this paper, we propose an algorithm that provide services to consumers who want to conduct business by scientifically and systematically analyzing the number of pedestrians in a specific area over a specific period of time. In this paper, we proposed the algorithm to analyze the commercial area using the pedestrian-detect algorithm in the particular region using YOLO, one of the deep learning techniques. And with one image per minute in the images, the number of pedestrians is identified and this information is used for the analysis of business district on interesting area and time, systematically and objectively.

• Archives of design research
• /
• v.20 no.3 s.71
• /
• pp.203-214
• /
• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• The Journal of Korean Institute of Information Technology
• /
• v.16 no.12
• /
• pp.75-83
• /
• 2018

Recently, autonomous vehicles have been actively studied. Pedestrian detection and recognition technology is important in autonomous vehicles. Pedestrian detection using CNN(Convolutional Neural Netwrok), which is mainly used recently, generally shows good performance, but there is a performance degradation depending on the environment of the image. In this paper, we propose a pedestrian detection system applying long-term memory structure of hippocampal neural network based on CNN network with LGP-FL (Local Gradient Pattern-Feature Layer) added. First, change the input image to a size of $227{\times}227$. Then, the feature is extracted through a total of 5 layers of convolution layer. In the process, LGP-FL adds the LGP feature pattern and stores the high-frequency pattern in the long-term memory. In the detection process, it is possible to detect the pedestrian more accurately by detecting using the LGP feature pattern information robust to brightness and color change. A comparison of the existing methods and the proposed method confirmed the increase of detection rate of about 1~4%.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.93-102
• /
• 2023

This study conducted an effect evaluation before and after the installation of a vehicle information guidance system that provides drivers with information about vehicle speed and the presence or absence of pedestrians near pedestrian crossings. There are three types of scenarios: when no information is provided to the driver (S1), when only the vehicle driving speed is provided (S2), and when pedestrians are present on the pedestrian crossing and when both vehicle driving speeds are provided (S3). did. As a result of the survey, the speed reduction rate of the vehicle was found to be about 0.4~0.7km greater in S2 and S3 that provide information to the driver than in scenario S1. In addition, in the scenario S3, the speed reduction rate is 0.2km higher than that in the case where there are pedestrians near the pedestrian crossing, which further reduces the vehicle speed. Statistical analysis also showed that there was a difference in the speed reduction rate of the average vehicle for the three scenarios, and that the speed reduction rate was large in the presence of pedestrians.

• Science of Emotion and Sensibility
• /
• v.13 no.1
• /
• pp.197-206
• /
• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.