• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.93-101
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• 2011

In 2008, Korea has observed total 215,822traffic accidents Although the number has decreased since then, the crash rate is still higher than those of other advanced countries. In particular, high rate of pedestrian accidents occurred on urban streets is recognized as a serious problem. The previous studies, however, are not entirely considerate of accident factors by accident type. Inspired by the fact, this study analyzes factors affecting traffic accident by accident type. Using the accident data collected on urban streets in Seodaemun-gu, this paper classifies the accidents into two groups (i.e., vehicle-vs-vehicle and vehicle-vs-person crashes), and analyzes relationships between severity and exogenous variables. For the analysis, Structural Equation Modeling (SEM) is employed to estimate relationships among exogenous factors of traffic accident by each type on urban streets. The resulting model reveals that roadway related factors are highly correlated with the severity of vehicle-vs-vehicle crashes whereas environment factors are with vehicle-vs-person crashes.

• Journal of Platform Technology
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• v.6 no.3
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• pp.10-16
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• 2018

Bicycle shares road with various traffic elements like car, pedestrian and, the number of bicycle user is increasing in recent. Therefore, bicycle accident continuously increases. Especially in complex traffic environment, bicycle accident which collides with moving object such as pedestrian occupies many parts of bicycle accident in the reason that the cyclist does not recognize moving object. In this paper, to reduce or avoid the bicycle accident, we propose the architecture of bicycle collision avoidance system in which that cyclist can get the information about moving object by connecting bicycle to network of vehicles and does some action for avoiding collision. In our architecture, when traffic element such as car recognizes moving object, it decides the moving direction of object, and transfers information about moving direction via vehicles network. Bicycle collision avoidance system from our proposed architecture receives this information, and alerts to cyclist when the moving object influences the safety of bicycle.

• International Journal of Highway Engineering
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• v.11 no.2
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• pp.17-25
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• 2009

The goal of this study is to develop Logistic regression model by accident location(entry section, exit section, inside intersection and pedestrian crossing section). Based on the accident data of Chungbuk Provincial Police Agency(2004$\sim$2005) and the field survey data, the geometric elements, environmental factor and others related to traffic accidents were analyzed. Developed models are all analyzed to be statistically significant(chi-square p=0.000, Nagelkerke $R^2$=0.363$\sim$0.819). The models show that the common factors of accidents are the traffic volume(ADT), distant of crossing and exclusive left turn lane, and the specific factors are the minor traffic volume(inside intersection model) and U-turn of main road(pedestrian crossing model). Hosmer & Loineshow tests are evaluated to be statistically significant(p$\geqq$0.05) except the entry section model. The correct classification rates are also analyzed to be very predictable(more than 73.9% to all models).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.90-100
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• 2017

This paper investigates pedestrian-thrown distance pattern by pedestrian-vehicle collision position by madymo-simulation. The simulation were performed for every 2.5 cm interval between center and edge of bumper for various vehicle speeds and vehicle shapes. As a result, two critical points where thrown distance change rapidly were found. First critical point locate where pedestrian's shoulder do not contact the vehicle. Second point locate where the center of gravity of pedestrian are close to edge of bumper. Between 1st and 2nd critical points, thrown distance decrease rapidly where collision points move to the edge of vehicle. In other cases, the thrown distance does not change rapidly. This result gives more accurate guideline for pedestrian collision in traffic safety.

• International Journal of Highway Engineering
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• v.20 no.1
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• pp.127-135
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• 2018

PURPOSES : Traffic cameras have been installed to reduce traffic accidents. The effectiveness of traffic cameras has been proved by dozens of studies, but recently questions over its effectiveness have been raised by a series of studies. In this study, the effectiveness of traffic cameras was analyzed with a focus on different road environments. METHODS : The effectiveness of the traffic cameras was analyzed by extracting the occurence frequency before and after camera installation. The effect of reduction was analyzed comprehensively considering the installation position, monitoring direction, and surrounding environment of traffic cameras. RESULTS : The result of this study is as follows. First, the installation of cameras in an area with relatively low accidental traffic was more effective. Secondly, the effect of camera installation on car-to-pedestrian collisions was better than that of car-to-car collisions. Thirdly, accidents tended to occur more frequently when cameras were installed in front of the accident-prone owing to the negative spill-over effect. CONCLUSIONS : The result can be used to guide placement of traffic cameras. Moreover, the installation of cameras with consideration of the road environment is expected to contribute to a reduction in traffic fatalities.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.437-447
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• 2020

Following the extension of human life expectancy, the number of elderly traffic accidents that have been increasing at a rapid pace since 2018 has also emerged as a social problem. The traffic accident rate among those aged 65 and older is increasing, but traffic safety policies are insufficient. Based on the analysis of traffic accident status for senior citizens and traffic accident for the past five years from 2014, the reduction plan is to be presented in three main aspects. First, the system needs systematic management by strengthening the system of senior citizens' transport policy departments and driver's license for senior citizens in government agencies, such as the United States, Britain and Japan, from an institutional perspective, so that the walking time and crosswalk traffic environment for the vulnerable should be improved from an environmental perspective. In addition, in human terms, the ability to cope with real-time changes in traffic conditions should be enhanced by training transportation safety experts to secure the effectiveness of education for elderly drivers and by strengthening safety education for those with driver's license and expanding experienced traffic safety facilities to enhance the ability of senior citizens to cope with the changing traffic conditions in real time.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.576-582
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• 2016

Currently, every person possesses a smart phone due to the development of the IT industry. However, crosswalk pedestrian accidents have been sharply increasing due to smart phone use. If a traffic light can recognize smart phones when a smart-phone user approaches and arrives at a given sign, many accidents could be reduced by using beacon signals. Before the era of smart phones, the accident rate involving cell phone use was relatively low. Nevertheless, when considering the development of IT equipment that produces a threat to human life, government cannot regulate smart phone use outside. The purpose of this paper is to indirectly warn a smart phone user in order to reduce the accident rates.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.31-39
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• 2008

Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. The accurate traffic accident prediction model requires not only understanding of the factors that cause the accident but also having the transferability of the model. So, this paper suggest the traffic accident diagram using CART(Classification And Regression Tree) analysis, developed Model is compared with the existing accident prediction models in order to test the goodness of fit. The results of this study are summarized below. First, traffic accident prediction model using CART analysis is developed. Second, distance(D), pedestrian shoulder(m) and traffic volume among the geometrical factors are the most influential to the traffic accident. Third. CART analysis model show high predictability in comparative analysis between models. This study suggest the basic ideas to evaluate the investment priority for the road design and improvement projects of the traffic accident blackspots.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.131-136
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• 2010

This study deals with the accident models of arterial link sections by vehicle type. The objectives are to analyze the characteristics of accidents, and to develop the models by type. In pursuing the above, this study uses the data of 414 accidents occurred on 24 major arterial links in 2007. The main results analyzed are as follows. First, the number of accidents is analyzed to account for about 47% in passenger car, 15% in SUV and 10% in trucks. Second, 3 Poisson regression models which are all statistically significant are developed using passenger car, SUV and truck as dependant variables. Finally, AADT and the number of traffic islands as common variables, and the number of pedestrian crossings, lanes, connecting roads, intersections(4-Leg), rate of medians and the number of bus stops as specific variables of the models are selected.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.162-164
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• 2022

Efforts are being made to prevent traffic accidents within the child protection zone. Efforts are being made to prevent accidents by enacting safety facilities and laws to prevent traffic accidents in the school zone. However, traffic accidents in school zones continue to occur. If the driver can know the situation in the child protection zone in advance, accidents can be reduced. In this paper, we design a camera that eliminates blind spots in school zones and a number recognition camera system that can collect pre-traffic information. Design a LIDAR system that recognizes vehicle speed and pedestrians. Design an LED guidance system that delivers information to drivers without smart devices. We study time series analysis and artificial intelligence algorithms that collect and process pedestrian and vehicle information recognized by cameras and LIDAR. In the artificial intelligence traffic accident prevention system learned by deep learning, before entering the school zone, the school zone information is sent to the driver through the Force Push Service and the school zone information is delivered to the driver on the LED sign. try to reduce accidents.