• 대한토목학회논문집
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• 제38권2호
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• pp.283-294
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• 2018

정확한 보행자 지체 모형은 보행자 중심의 신호교차로 평가에 있어 핵심 요소이다. 신호화된 보행자 횡단보도에서 녹색시간동안 보행자 횡단 행태는 매우 다양하며, 보행자의 도착 행태는 임의도착과 보행군으로 구성된다. 따라서 정확한 보행자 지체를 산정하기 위해서는 보행자의 횡단과 도착 행태가 고려되어야 한다. 이러한 필요성에도 불구하고, 도로용량편람(HCM)은 보행자 도착과 횡단 행태를 반영하지 않은 간략한 보행자 지체모형을 권고하고 있다. 이러한 이유로, 보행자 중심적인 신호교차로의 설계 및 운영에 대한 의사결정을 위해서는 다양한 신호화된 단일 횡단보도 및 신호교차로에 적합한 보행자 지체 모형이 요구되고 있다. 본 연구에서는 보행자의 도착과 횡단 행태를 기반으로 새로운 보행자 지체모형을 제시한다. 제안되는 모형은 신호화된 단일 횡단보도 보행자 지체모형과 신호교차로 보행자 지체모형으로 구성된다. 단일 횡단보도 지체모형은 보행자 녹색시간 동안 보행자 횡단 행태를 기반으로 개발되었다. 신호교차로 지체모형은 보행자 횡단과 보행군 도착 행태를 기반으로 개발되었다. 수치 모의실험을 통한 평가결과, 제안되는 지체모형은 다양한 보행자 횡단과 도착 행태를 고려하기 때문에 HCM 모형의 과대/과소추정 문제를 효과적으로 해결할 수 있음을 보였다.

• 한국도로학회논문집
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• 제16권3호
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• pp.101-107
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• 2014

PURPOSES : This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS : To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS : The optimal model for pedestrian accidents is evaluated to be Tobit model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4379-4397
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• 2017

Three different improvements of the Velocity-based model were proposed in a minimal velocity-based pedestrian model. The improvements of the models are based on the different agent forms. The different representations of the agent lead to different results, in this paper, we simulated the pedestrian movements in some typical scenes by using different agent forms, and the agent forms included the circles with different radiuses, the ellipse and the multi-circle stand for one pedestrian. We have proposed a novel model of pedestrian dynamics to optimize the simulation. Our model specifies the pedestrian behavior using a dynamic ellipse, which is parameterized by their velocity and can improve the simulaton accuracy. We found a representation of the pedestrian much closer to the reality. The phenomena of the self-organization can be observable in the improved models.

• 한국도로학회논문집
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• 제16권4호
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• pp.111-118
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• 2014

PURPOSES: The purposes are to analyze the pedestrian accident severity and to develop the accident models by arterial road function. METHODS: To analyze the accident, count data and ordered logit models are utilized in this study. In pursuing the above, this study uses pedestrian accident data from 2007 to 2011 in Cheongju. RESULTS : The main results are as follows. First, daytime, Tue.Wed.Thu., over-speeding, male pedestrian over 65 old are selected as the independent variables to increase pedestrian accident severity. Second, as the accident models of main and minor arterial roads, the negative binomial models are developed, which are analyzed to be statistically significant. Third, such the main variables related to pedestrian accidents as traffic and pedestrian volume, road width, number of exit/entry are adopted in the models. Finally, Such the policy guidelines as the installation of pedestrian fence, speed hump and crosswalks with pedestrian refuge area, designated pedestrian zone, and others are suggested for accident reduction. CONCLUSIONS: This study analyzed the pedestrian accident severity, and developed the negative binomial accident models. The results of this study expected to give some implications to the pedestrian safety improvement in Cheongju.

• 국토계획
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• 제54권3호
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• pp.106-118
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• 2019

In order to develop pedestrian navigation service that provides optimal pedestrian routes based on pedestrian satisfaction levels, it is required to develop a prediction model that can estimate a pedestrian's satisfaction level given a certain condition. Thus, the aim of the present study is to develop a pedestrian satisfaction prediction model based on three machine learning algorithms: Logistic Regression, Random Forest, and Artificial Neural Network models. The 2009, 2012, 2013, 2014, and 2015 Pedestrian Satisfaction Survey Data in Seoul, Korea are used to train and test the machine learning models. As a result, the Random Forest model shows the best prediction performance among the three (Accuracy: 0.798, Recall: 0.906, Precision: 0.842, F1 Score: 0.873, AUC: 0.795). The performance of Artificial Neural Network is the second (Accuracy: 0.773, Recall: 0.917, Precision: 0.811, F1 Score: 0.868, AUC: 0.738) and Logistic Regression model's performance follows the second (Accuracy: 0.764, Recall: 1.000, Precision: 0.764, F1 Score: 0.868, AUC: 0.575). The precision score of the Random Forest model implies that approximately 84.2% of pedestrians may be satisfied if they walk the areas, suggested by the Random Forest model.

• 한국안전학회지
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• 제29권5호
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.

• 한국ITS학회 논문지
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• 제8권3호
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• pp.131-138
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• 2009

본 연구의 목적은 CA(Cellular Automata)이론을 기반으로 행위자기반(agent-based) 보행시뮬레이션 모델을 개발하고, 개발된 모델을 보행시설 설치 실험에 적용하여보는 것이다. 이를 위하여 본 연구에서는 보행교통류에 CA이론이 적용된 모델을 검토하고, Fence라는 보행시설이 보행자의 통행속도에 미치는 영향을 분석하기 위해 실험을 계획하고 CA보행자 모델을 구축하였다. 구축된 CA보행자 모델은 초기화, 보행자 발생 유입, 측방이동, 전방이동의 하위모델로 구성되어 있다. 실험결과 Fence를 설치했을 때의 보행속도가 Fence를 설치하지 않았을 때의 보행속도보다 높게 나타나, 통행 방향이 다른 보행자가 혼재되어 있을 경우 Fence를 설치하지 않았을 때의 보행속도보다 높게 나타나, 통행 방향이 다른 보행자가 혼재되어 있을 경우 Fence를 설치하는 것이 효과적인 것으로 나타났다. 또한, Fence의 설치는 매우 혼잡한 상황에서보다 적당한 혼잡상태에서 더 큰 것으로 분석되었다.

• 한국기계가공학회지
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• 제7권4호
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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.

• 한국도로학회논문집
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• 제12권4호
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• pp.11-16
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• 2010

보행교통류를 주제로 다양한 연구들이 진행되었지만 초기의 보행연구는 차량의 교통류이론을 그대로 적용하여 해석하기도 하였다. 최근 보행교통류에 대한 다양한 모형들이 제시되고 있으며, 특히 CA모형은 보행교통류를 위한 시뮬레이션 모형으로 빈번하게 사용되고 있다. 대표적인 CA 모형으로 가스입자의 움직임을 이용하여 양방향의 보행교통류를 설명하기도 하였는데 초기에는 정방형의 Gas-lattice 모형이 제안되었으며 이후에 정육방 Gas-lattice 모형을 이용하여 보행자의 움직임과 회피를 묘사하기도 하였다. 하지만 이러한 모형들은 보행자의 움직임을 편의임의보행으로 가정하였기 때문에 단일방향으로의 움직임만을 설명할 수 있었다. 본 연구에서 제시된 MLPM(the Multi-Layer Pedestrian Model)은 어떤 공간에서 복수개의 기종점을 가진 경우에도 현실적인 보행자의 움직임을 설명할 수 있는 모형이다.

• 대한임베디드공학회논문지
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• 제18권5호
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• pp.259-265
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• 2023

Pedestrian detection is used to effectively detect pedestrians in various situations based on deep learning. Pedestrian detection has difficulty detecting pedestrians due to problems such as camera performance, pedestrian description, height, and occlusion. Even in the same pedestrian, performance in detecting them can differ according to the height of the pedestrian. The height of general pedestrians encompasses various scales, such as those of infants, adolescents, and adults, so when the model is applied to one group, the extraction of data becomes inaccurate. Therefore, this study proposed a pedestrian detection method that fine-tunes the pedestrian area by Refining Layer and Feature Concatenation to consider various heights of pedestrians. Through this, the score and location value for the pedestrian area were finely adjusted. Experiments on four types of test data demonstrate that the proposed model achieves 2-5% higher average precision (AP) compared to Faster R-CNN and DRPN.