• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.2
• /
• pp.283-294
• /
• 2018

An accurate pedestrian-delay model is essential for the pedestrian-oriented evaluation of signalized intersection (SI). The crossing behaviors of pedestrians at signalized pedestrian crosswalks (SPCs) are various, and their arrival behaviors consist of two types, random and platoon. It is natural, hence, that the behaviors of pedestrian crossing and arrival should be considered in order to estimate accurate pedestrian delay. Despite this necessity, a simple pedestrian-delay model that cannot explain these behaviors of pedestrian movements is still recommended in Highway Capacity Manual (HCM). For these reasons, a pedestrian-delay model, suitable for various SPCs and SIs, is required to make pedestrian-oriented decisions on the design and operation of various SPCs and SIs. This paper proposes a novel pedestrian-delay model that is based on the behaviors of pedestrian crossing and arrival. The proposed model consists of two sub models: the one for SPC and the other for SI. The SPC delay model was developed based on the behaviors of pedestrian crossing during pedestrian green time. The SI delay model was designed based on the behaviors of pedestrian crossing and platoon arrival. The results of a numerical simulation showed that the proposed delay model can successfully overcome the under- and overestimation problems of the HCM model with explaining various behaviors of pedestrian crossing and arrival.

• International Journal of Highway Engineering
• /
• v.16 no.3
• /
• pp.101-107
• /
• 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)
• /
• v.11 no.9
• /
• pp.4379-4397
• /
• 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.

• International Journal of Highway Engineering
• /
• v.16 no.4
• /
• pp.111-118
• /
• 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.

• Journal of Korea Planning Association
• /
• v.54 no.3
• /
• pp.106-118
• /
• 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.

• Journal of the Korean Society of Safety
• /
• v.29 no.5
• /
• pp.154-159
• /
• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.3
• /
• pp.131-138
• /
• 2009

The purpose of this paper is the development of an agent-based pedestrian simulation model. The simulation model is based on the Cellular Automata theory. The model consists of four components: initialization, pedestrian generation, lateral movement, and front movement components. We have applied this model for experiment about pedestrian facility. In particular, we have experimented how the installation of fence is effective to resolve conflict pedestrian movements in different directions. We have found that the installation of the fence as a pedestrian facility can divide conflict moving pedestrians effectively. We have also found that the effect of the fence is bigger in slightly congested pedestrian flows than in severely congested pedestrian flows.

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

• International Journal of Highway Engineering
• /
• v.12 no.4
• /
• pp.11-16
• /
• 2010

Various researches have been performed on the topic of pedestrian traffic flow. At the beginning, the modeling and simulation method for the vehicular traffic flow was simply applied to pedestrian traffic flow. Recently, CA based simulation models are frequently applied to pedestrian flow analysis. Initially, the square Lattice Model is a base model for applying to pedestrians of counterflow and then Hexagonal Lattice Model improves its network as a hexagonal cell for more realistic movement of the avoidance of pedestrian conflicts. However these lattice models express only one directional movement because they express only one directional movement. In this paper, MLPM (the Multi-Layer Pedestrian Model) is suggested to give various origins and destinations for more realistic pedestrian motion in some place.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.259-265
• /
• 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.