• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.202-211
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• 1996

A number of typical type of steel-box pedestrian bridges are constructed in the metropolitan highway or heavy traffic urban area. Although it has the advantage of speedy construction because of its simple structural form and prefabricated erection method, it has been reported that many of these bridges are deteriorated or damaged and thus are in the state such that it would give unsafe and uncomfortable feeling to pedestrians. In the paper, for the realistic assessment of safety and residual earring-capacity of deteriorated and/or damaged steel box pedestrian bridges, an interactive non-linear limit state model are formulated based on the von Mises' combined stress yield criterion. It is demonstrated that the proposal model is effective for the reliability-based safety assessment and residual carrying-capacity evaluation of steel-box pedestrian bridges. In addition, this study suggests an effective and practical field load test method for pedestrian bridges.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.734-741
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• 2020

This article proposes a new pedestrian avoidance algorithm for social robots that coexist and communicate with humans and do not induce stress caused by invasion of psychological safety distance(Social Distance). To redefine the pedestrian model, pedestrians are clustered according to the pedestrian's gait characteristics(straightness, speed) and a social distance is defined for each pedestrian cluster. After modeling pedestrians(obstacles) with the social distances, integrated navigation algorithm is completed by applying the newly defined pedestrian model to commercial obstacle avoidance and path planning algorithms. To show the effectiveness of the proposed algorithm, two commercial obstacle avoidance & path planning algorithms(the Dynamic Window Approach (DWA) algorithm and the Timed Elastic Bands (TEB) algorithm) are used. Four cases were experimented in applying and non-applying the new pedestrian model, respectively. Simulation results show that the proposed algorithm can significantly reduce the stress index of pedestrians without loss of traveling time.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.194-205
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• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

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

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.37-49
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• 2015

In Space Syntax, the greater the degree of integration between separate links, the greater the links' accessibility from the target network. As such, planning pedestrian walks so that links with high degrees of integration are connected, or else inducing high integration value land use are both valid options. The travel distribution model reflects how walking demand, or more specifically, the pedestrian, partakes in route choosing behavior that minimizes select criteria, notably level of discomfort, as measured using travel distance and time. The model thus demonstrates travel patterns associated with demand pertaining to minimization of discomfort experienced by the pedestrian. This research introduces a method that integrates Space Syntax and the pedestrian travel distribution model. The integrated model will determine whether regions with high degrees of integration are actually being used as pivots for pedestrian demand movement, as well as to explain whether the degree of integration is sustained at an appropriate level while considering actual movement demand. As a means to develop the integrated model, a method that combines display of the visibility of the space syntax network and road-divided links is proposed. The pedestrian travel distribution model also includes an alternative path finding mechanism between origin and destination, which allows for uniform allocation of demand.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.153-164
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• 2009

This Paper presents the severity analysis result of the year 2006 national pedestrian crashes using the data base of 37,589 records prepared for the National Police Bureau. A set of attributing factors considered to affect pedestrian crash patterns were selected, and their contributing effects were investigated by applying the Ordered Logit Model. This model was selected because this model has been able to afford satisfactory results when the dependent variable involved ordered severity levels; fatal, injury, and property- damage-only in this investigation. The investigation has unveiled the followings; First, the pedestrian crash patterns were dependent upon human -drivel and pedestrian- characteristics including gender, age, and drinking conditions. Second, other contributing factors included vehicle, roadway geometric, weather, and hour of day characteristics. Third, seasonal effect was not contributive to crash patterns. Finally, the application of the Ordered Logit Model facilitated the ordered severity level analysis of the pedestrian crash data. This paper concludes that conventional wisdom on the pedestrian crash characteristics is largely truthful. However, this conclusion is limited only to the data used in this analysis, and further research is required for its generalization.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.3-14
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• 2018

The aim of this study is to propose a method for calculating the weight of walking energy in ERAM model by calculating it for the analysis of vertical and horizontal spaces in a building. Conventional theories on the space analysis in the field of architectural planning predict the pedestrian volume of network spaces in urban street or in two-dimensional plane within a building, however, for vertical and horizontal spaces in a building, estimates of the pedestrian volume by those theories are limited. Because in the spatial syntax and ERAM model have been applied weights such as the spatial depth, adjacent angles, and physical distances available only to the two-dimensional same layer or plane. Therefore, the following basic assumptions and analysis conditions in this study were established for deriving a predictor of pedestrian volume in vertical and horizontal spaces of a building. The basic premise of space analysis is not to address the relationship between the pedestrian volume and the spatial structure itself but to the properties of spatial structure connection that human beings experience. The analysis conditions in three-dimensional spaces are as follows : 1) Measurement units should be standardized on the same scale, and 2) The connection characteristics between spaces should influence the accessibility of human beings. In this regard, a factor of walking energy has the attributes to analyze the connection of vertical and horizontal spaces and satisfies the analysis conditions presented in this study. This study has two implications. First, this study has shown how to quantitatively calculate the walking energy after a factor of walking energy was derived to predict the pedestrian volume in vertical and horizontal spaces. Second, the method of calculating the walking energy can be applied to the weights of the ERAM model, which provided the theoretical basis for future studies to predict the pedestrian volume of vertical and horizontal spaces in a building.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.103-113
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• 2005

A pedestrian accident is generally less fully understood than the 'typical' car-to-car collision. For this reason, the analysis of the pedestrian accident is, in many respects, more complicated and demanding. The purpose of this study is to identify clearly the impact point that is the main subject of struggle in pedestrian accidents. In order to develop the model, it is very significant to classify actual accident data including impact velocity. vehicle damage and injury scale of pedestrian. These data were collected from three local branches of RTSA(Road Traffic Safely Authority). The number of collected data were 34 cases and 61.7% of them were fatal accidents. In consequence of analyzing the data by statistical method, it revealed that there is correlation between impact velocity and throw distance. It, also shows that the impact velocity has strong linear correlation to vehicle damage and injury scale. Consequently, reconstruction analysis models of pedestrian accidents considering in local circumstances(such as the physical characteristics of pedestrians and vehicles) was developed However. it is difficult to apply the result of this study to all sorts of pedestrian accidents, because the actual accident data which were used to develop the model were limited. To overcome this limitation, it is necessary to develop an analysis model applicable to diverse circumstances with a wide range of pedestrian accident data on a national basis.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.61-68
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• 2022

In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model's test performance are presented.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.8
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• pp.101-109
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• 2019

Korea's transportation paradigm is shifting from a vehicle-oriented transportation plan to a pedestrian-friendly environment that emphasizes walking safety. However, the level of pedestrian traffic accidents in Korea is still high and serious. The purpose of this study is to investigate factors affecting the severity of pedestrians traffic accidents using the multilevel logistic regression model based on 2015-2017 pedestrian accidents data provided by the Traffic Accident Analysis System(TAAS). The main results of the multilevel logistic regression model showed that 89% of pedestrian traffic accidents in Seoul were explained by individual characteristics such as drivers and pedestrians, and 11% were explained by neighborhood environmental characteristics. The results are as follows : In the individual characteristics such as pedestrians and drivers, the older the pedestrians and the drivers, the higher the traffic accident severity. The severity of traffic accidents was high when the pedestrians were female and the drivers were male. In the case of accident types, traffic accidents were more serious in the cases of heavy vehicles, inclement weather, and occurring at intersections and crosswalks. The results of the neighborhood environmental characteristics are as follows. The intersection density and the crosswalk density tended to reduce the severity of traffic accidents. On the other hand, the traffic light density and the school zones were founded to related to the higher level of traffic accident severity. This study suggests that both individual and neighborhood environmental characteristics should be considered together to prevent and reduce the severity of pedestrian traffic accidents.