• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.81-92
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• 2002

An automobile crash with a pedestrian generates a trajectory which is crucial to identify the cause of the crash. Previous researches have been carried out for pedestrian movement using simple explicit formulae. The formulae are derived from elementary physics. Therefore, they could not sufficiently include variables of a vehicle and a pedestrian. To overcome such a limitation, a simulation is utilized for the pedestrian behavior in crash environment. A dynamic software called MADYMO is utilized for the simulation. A simulation model is established. The automobile body and a dummy are modeled with rigid bodies, joints and springs. The simulation results are compared with those from explicit formulae. It is found that the explicit formulae did not fit to pedestrian conditions. Simulations are performed for various velocities of automobiles. Results are discussed for the usage of the simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2310-2325
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• 2016

In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.115-120
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• 2008

The fatalities of pedestrian accounted for about 40.0% of all fatalities in Korea (2005 year). In pedestrian involved accident, the most important data to inspect accident is throw distance of pedestrian. The throw distance of pedestrian can be influenced by many variables, such as vehicular frontal shape, vehicular impact speed, the offset of impact point, the height of pedestrian, and road condition. The trajectory of pedestrian after collision can be influenced by vehicular frontal shape classified into sedan type, box type, SUV type and van type. Many studies have been done about pedestrian accident with passenger car model and bus model for simple factors. But the study of pedestrian accident by van type vehicle was much insufficient, and even that the influence of multiple factors such as the offset of impact point was neglected. In this paper, a series of pedestrian kinetic simulation were conducted to inspect relationship between throw distance and multiple factors with using PC-CRASH s/w, a kinetic analysis program for a traffic accident for van type. By based on the simulation results, multi-variate regression was conducted, and regression equation was presented.

• Journal of Power System Engineering
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• v.13 no.5
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• pp.76-81
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• 2009

The fatalities of pedestrian account for about 21.2% of all fatalities at 2007 year in Korea. To reconstruct exactly the accident, it is important to calculate the throw distance of pedestrian in car to pedestrian accident. The frontal shape of SUV vehicle is dissimilar to passenger car and bus, so the trajectory and throw distance of pedestrian by SUV vehicle is not the same of passenger car and bus. The influencing on it can be classified into the factors of vehicle and pedestrian, and road factor. It was analyzed by PC-CRASH for simulation, and SPSS s/w was used for regression analysis. From the simulation results, the maximum impact energy of multi-body of pedestrian was occurred to that of torso body at the same time. And the throw distance increased with the increasing of impact velocity, and decreased with the increasing of impact offset. Also it decreased with the increasing of velocity of pedestrian at accident, and the throw distance of wet road was longer than that of dry road. Finally, the regression analysis model of SUV(Nissan Pathfinder type)vehicle in car to pedestrian accident was as follows; $$disti_i=-0.87-0.11offseti_i+0.69speed_i-4.27height_i+0.004walk_i+0.63wet_i+{\epsilon}_i$$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1244-1253
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• 2021

In this paper, we propose a method for predicting in advance whether pedestrians will enter the hazardous area after the current time using the pedestrian trajectory prediction method and an efficient simplification method of the trajectory prediction network. In addition, we propose a method to apply KD(Knowledge Distillation) to a small network for real-time operation in an embedded environment. Using the correlation between predicted future paths and hazard zones, we determined whether to enter or not, and applied efficient KD when learning small networks to minimize performance degradation. Experimentally, it was confirmed that the model applied with the simplification method proposed improved the speed by 37.49% compared to the existing model, but led to a slight decrease in accuracy. As a result of learning a small network with an initial accuracy of 91.43% using KD, It was confirmed that it has improved accuracy of 94.76%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3769-3789
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• 2018

Social pedestrian groups are the basic elements that constitute a crowd; therefore, detection of such groups is scientifically important for modeling social behavior, as well as practically useful for crowd video understanding. A social group refers to a cluster of members who tend to keep similar motion state for a sustained period of time. One of the main challenges of social group detection arises from the complex dynamic variations of crowd patterns. Therefore, most works model dynamic groups to analysis the crowd behavior, ignoring the existence of stationary groups in crowd scene. However, in this paper, we propose a novel unified framework for detecting social pedestrian groups in crowd videos, including dynamic and stationary pedestrian groups, based on spatiotemporal-oriented energy measurements. Dynamic pedestrian groups are hierarchically clustered based on energy flow similarities and trajectory motion correlations between the atomic groups extracted from principal spatiotemporal-oriented energies. Furthermore, the probability distribution of static spatiotemporal-oriented energies is modeled to detect stationary pedestrian groups. Extensive experiments on challenging datasets demonstrate that our method can achieve superior results for social pedestrian group detection and crowd video classification.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.89-92
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• 2022

본 논문에서는 딥러닝 모델 기반 보행자의 GPS 경로를 예측하는 시스템을 제안한다. 다양한 경로 예측 방식들 중 본 논문은 GPS 데이터 기반 경로 예측 연구이다. 시계열 데이터인 보행자의 GPS 경로를 학습하여 다음 경로를 예측하도록 하는 딥러닝 모델 기반 연구이다. 본 논문에서는 보행자의 GPS 경로를 딥러닝 모델이 학습할 수 있도록 데이터 구성 방식을 제시하였으며, 예측 범위에 큰 제약이 없는 예측 딥러닝 모델을 제안한다. 본 논문의 딥러닝 모델에 적합한 파라메터들을 제시하였으며, 우수한 예측 성능을 보이는 결과를 제시한다.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1309-1323
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• 2020

Crowd evacuation simulation is an important research issue for designing reasonable building layouts and planning more effective evacuation routes. The social force model (SFM) is an important pedestrian movement model, and is widely used in crowd evacuation simulations. The model can effectively simulate crowd evacuation behaviors in a simple scene, but for a multi-obstacle scene, the model could result in some undesirable problems, such as pedestrian evacuation trajectory oscillation, pedestrian stagnation and poor evacuation routing. This paper analyzes the causes of these problems and proposes an improved SFM for complex multi-obstacle scenes. The new model adds navigation points and walking shortest route principles to the SFM. Based on the proposed model, a crowd evacuation simulation system is developed, and the crowd evacuation simulation was carried out in various scenes, including some with simple obstacles, as well as those with multi-obstacles. Experiments show that the pedestrians in the proposed model can effectively bypass obstacles and plan reasonable evacuation routes.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.85-93
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• 2011

The width of sidewalk is one of the important factors constructing a pleasant pedestrian environment. The procedure for sidewalk width design based on the Level of Service is suggested in Korea Highway Capacity Manual. However, this manual does not give a difference between the sidewalk on the street with the passage of the subway, therefore, the different flow characteristic of these places is not appropriately reflected. Though the pedestrian flow in the subway encounters a frequent stop and go situation as like the platoon of vehicles, the similar condition is rarely observed at the urban streets. The new measure of LOS for sidewalk is in need. The study reviewed the prominent measure of LOS and carried out the outdoor experiment to evaluate the new measure. Particularity, GPS was used to collect the pedestrian foot path trajectory for the quantitative evaluation and the results from quantitative and qualitative are compared.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.315-321
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• 2017

This paper is a study on the design and realization of Pedestrian navigation service system for the visually impaired. As it is an user interface considering visually impaired, voice recognition functioned smartphone was used as the input tool and the Osteoacusis headset, which can vocally guide directions while recognizing the surrounding environment sound, was used as the output tool. Unlike the pre-existing pedestrian navigation smartphone apps, the developed system guides walking direction by the scale of the left and right stereo sound of the headset wearing, and the voice guidance about the forked or curved path is given several meters before according to the speed of the user, and the user is immediately warned of walking opposite direction or proceeding off the path. The system can acquire stable and reliable directional information using the motion tracker with the dynamic heading accuracy of 1.5 degrees. In order to overcome GPS position error, we proposed a robust trajectory planning algorithm for position error. Experimental results for the developed system show that the average directional angle error is 6.82 degrees (standard deviation: 5.98) in the experimental path, which can be stated that it stably navigated the user relatively.