• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.5-6
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• 2019

최근 보행자 행태를 반영한 미시적 시뮬레이션 분석이 가능하게 되었다. 차량 분석과 유사하게 보행자 행태 중 가장 빈번히 사용되는 것은 보행속도로 이는 횡단보도 보행자 녹색시간 산정과도 매우 밀접한 관계가 있다. 또한 보도의 밀도를 산정함에 있어서 보행자 속도는 중요한 역할을 담당한다. 이에 본 논문에서는 횡단보도의 보행자 속도를 실측하고, 이를 기반으로 미시적 시뮬레이션인 VISSIM의 주요 파라메타인 보행속도를 이용하여 역삼역 일대의 보행실태를 점검해 보았다. 분석에 사용된 보행속도 실측자료는 서울시 16개 횡단보도에서 조사되었으며, 연령별로 일반인(64세 이하)과 노인(65세 이상)을 구분하여 분석하였다.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.43-53
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• 2006

Pedestrian countdown signals were newly introduced to make Pedestrians feel more comfortable and safer in crossing the streets This Paper analysed pedestrian walking-speed through a before-after behavior study Data was collected from 22 sites. and the total number of pedestrians was 19,800. The results showed that the average Pedestrian walking-speed of existing pedestrian signal, an inverted triangle countdown signal and a numeric countdown signal were 1.44, 1.39 and 1.42m/sec. The difference between the three methods was statistically significant. The results showed that the distribution of the walking-speed of existing signal. an inverted triangle countdown signal and a numeric countdown signal were statistically Erlang(0.117, 10) distribution. Weibull(1.17, 3.72) distribution and Gamma(0.137, 8.18) distribution at 95% confidence level.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.7-18
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• 2001

The pedestrian signal systems operating presently could provide more time for the pedestrian to cross the street than the previous system, but it would increase the cycle length and cause longer delays at the signalized intersections. For instance, more than 80% of traffic signals would have to have the cycle length increased by 10sec in Daegu Metropolitan areas. Therefore. the purpose of this study is to propose a pedestrian traffic signal time that not only maintains the safety of the pedestrian but also reduces the traffic cycle length. The proposed pedestrian signal time is set to enable enough time for the elderly to cross and the flashing time is set low enough to deter the ordinary person. This new pedestrian signal time can reduce the traffic cycle length at intersections and prevent the Pedestrian crossing during flashing time. In addition to the flashing green should be changed to flashing red to warn the pedestrian he should not begin crossing as opposed to the flashing green which suggest he could cross. In this study, the speed of 1.1m/sec and 0.85m/sec are applied to the new proposed signal time for normal and elderly person respectively after analyzing data collected at Daegu Metropolitan area.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.106-118
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• 2014

The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.489-492
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• 2015

사용자의 위치기반 서비스에 대한 수요가 증가함에 따라 보행자의 현재 이동경로와 위치를 나타내는 '보행자 항법 시스템(PDR, Pedestrian Dead Reckoning)'에 관한 많은 연구들이 진행 중이다. 보행자 관성 항법 시스템은 IMU를 통해 데이터를 수신하여 각속도와 가속도 값을 구하고, 이 값을 토대로 사용자의 속도와 위치를 추정 한다. 또한 Zero-velocity(영속도)검출을 통해 누적되는 오차를 보정한다. 지금까지 대부분의 보행자 관성항법 시스템의 성능평가는 보행속도가 느리고 제한적인 상황에서 수행되었다. 하지만 이러한 상황은 보행자의 실제 보행상태를 반영하지 못한다. 본 논문에서는 다양한 보행속도에 따른 관성 항법 시스템의 성능을 실험하고 결과를 분석한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.54-61
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• 2016

This paper try to identify the minimum speed of vehicles in collision between pedestrian head and windshield at vehicle-pedestrian accidents. The MADYMO program was used with NF Sonata vehicle and pedestrian in height of 160cm, 170cm, and 180cm. From the simulation results, it was found that the minimum speed of vehicle was different for each pedestrian height : 49km/h for 160cm, 41km/h for 170cm, and 29km/h for 180cm. The results could be used in speed estimating process when there is a collision trace between pedestrian head and windshield at vehicle- pedestrian accident investigation.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.49-57
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• 2005

This study developed a methodology for estimating the fatality reduction by introducing technical regulation on pedestrian protection in pedestrian-vehicle collisions. Modeling a probabilistic pedestrian fatality model with logistic regression approach was one of keen interests, which employed in estimating the fatality reduction. Collision speed obtained from the accident reconstruction was used in the model development. The effects of fatality reduction, in case various Head Injury Criterion (HIC) and collision speeds are applied for the regulation. were presented as the major outcome of this study. It is expected that the outcome of this study would be an invaluable tool to assist in developing various technologies and policies for pedestrian protection.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.105-113
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• 2002

As the number of pedestrian accident increases, the reconstruction of an accident becomes important to find the source of the fault. Generally, accidents are reconstructed by the intuition of experts or primitive physics. A reconstruction method is proposed using sophisticated optimization technology. At first, a dynamic simulation model is established for the accident environment. Occupant analysis for automobile crashworthiness is employed. The situation before an accident is identified by optimization. The impact velocity and the position of the pedestrian are utilized as design variables. The design variables are found by minimizing the difference between the simulation and the real accident. The optimization process is performed by linking an occupant analysis program MADYMO to an optimization program VisualDOC. Since the involved analysis is dynamics and highly nonlinear, response surface method is selected for the optimization process. Problems are solved for various situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.202-210
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• 2019

This paper evaluated the performance of passenger vehicles with an AEB(Autonomous Emergency Braking) for various pedestrian-vehicle collision situations. The experiment was conducted at a speed of 30-60km/h on a 2017 3,000cc vehicle using a range of collision scenarios. The results showed that the test vehicle stopped before crashing a pedestrian dummy under all scenarios at 30km/h. The test vehicle reduced the speed but crashed the pedestrian dummy in all scenarios at 40-60km/h. From the paired t-test, there was a speed difference from the AEB system at a significant level of 0.05. In addition, the percentage of speed reduction was quite different for each scenario tested. It was concluded that the current AEB system can prevent pedestrian collisions at speed of 30km/h, but cannot prevent collisions with pedestrians at speed of 40-60 km/h.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.85-95
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• 2017

This study aims to identify the throw distance in terms of truck weight, bumper height, and speed in a truck and pedestrian collision, and to propose a model for throw distance estimates. For this purpose, a simulation analysis is performed using the PC-crash program with the following experiment conditions: Truck weight of 5t, 15t, and 25t, Bumper height from 0.3m to 0.6m by 0.1m, and speed from 10km/h to 100km/h by 10 km/h. Experimental results show that the truck speed and bumper height are found to be significant factors for pedestrian throw distance, but truck weight is not a significant factor. Also, a regression model is developed for pedestrian throw distance estimate from the multiple regression analysis. The adjusted $R^2$ value of the model is 93.3%, which is very good explanatory power.