• Journal of Auto-vehicle Safety Association
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• v.11 no.1
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• pp.30-35
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• 2019

KIDAS (Korean In-Depth Accident Study) is a data structure of accident investigation type, vehicle breakage and human injury database. A consortium of research institutes, universities, and medical institutions has been established and operated. KIDAS has the strongest difference from the TAAS (Traffic Accident Analysis System), which is the data of the National Police Agency, that it can grasp the injury information of passengers. In this study, the mean age and weight of the most frequent accident types in the KIDAS accident statistics were calculated to determine the degree of injury according to gender. Through the MADYMO analysis, it is aimed to grasp the difference of dummy injury using commercial dummy models and scaling models are currently used.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.1-9
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• 2024

In this paper, we propose a new approach by analyzing driver behavior and gaze changes within the vehicle in real-time to assess and predict the risk of traffic accidents. Utilizing data analysis and machine learning algorithms, this research precisely measures drivers' abnormal behaviors and gaze movement patterns in real-time, and aggregates these into an overall Risk Score to evaluate the potential for traffic accidents. This research underscores the significance of internal factors, previously unexplored, providing a novel perspective in the field of traffic safety research. Such an innovative approach suggests the feasibility of developing real-time predictive models for traffic accident prevention and safety enhancement, expected to offer critical foundational data for future traffic accident prevention strategies and policy formulation.

• International Journal of Highway Engineering
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• v.16 no.2
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• pp.119-129
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• 2014

PURPOSES : The purpose of this study is to develop the U-turn accident model at 4-legged signalized intersections in urban areas. METHODS : In order to analyze the characteristics of the accidents which are associated with U-turn operation at 4-legged signalized intersections in urban areas and develop an U-turn accident model by regression analysis, the tests of overdispersion and zero-inflation are conducted about the dependent variables of number of accidents and EPDO (Equivalent Property Damage Only). RESULTS : As their results, the Poisson model fits best for number of accident and the ZIP (Zero Inflated Poisson) fits best for EPOD, the variables of conflict traffic, width of opposing road, traffic passing speed are adopted as independent variable for both models. The variables of number of bus berths and rate of U-turn signal time at which the U-turn is permitted are adopted as independent variable only for EPDO. CONCLUSIONS : These study results suggest that U-turn would be permitted at the intersection where the width of opposing road is wider than 11.9 meters, the passing vehicle speed is not high and U-turn operation is not hindered by the buses stopping at bus stops.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.63-82
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• 1995

This paper deals with the forecasting model for traffic accident. Its objective is to develop the appropriate model to project the accident of Chung-Chong Region. Two types of models between motorization (M) and personal hazard (P) are tested : One is inverted-U (bell type) curve and the other is increasing (or decreasing) curve. The statiscal and sensitivity analyses show that exponential model (type III) and multiplicative model (type II) are well fit to the given cross-sectional and time-series accident data. The model projects that the fatality per 100, 000 persons of Chung-Chong region, when the motorization level (M) is 0.2, would be in the range between 18 and 77 persons. The paper concludes that the accident level is the function of motorization and the result of implementing the safety policy of a region.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.33-40
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• 2009

This study deals with the traffic accidents of elderly drivers. The objectives are to comparatively analyze the characteristics of accident between the elderly and other drivers, and to develop the models of traffic accidents. In pursuing the above, this paper gives particular attentions to testing the differences between the above two groups, and developing the models(Poisson and negative binomial regression) using the data of Cheongju 4-legged signalized intersections. The main results analyzed are as follows. First, the differences between the elderly and other drivers' accidents were clearly defined by the time of day, accident type, etc. Second, 3 accident models which were all statistically significant were developed. Finally, the differences between elderly and other drivers' models were comparatively analyzed using the common and specific variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.36-45
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• 2009

Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.161-170
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• 2008

This study deals with the accident models by vehicle type. The goal is to develop the accident models by vehicle type using the data of 143 4-legged signalized intersections in Cheongju. In pursuing the above, this study gives the particular attentions to explaining the relationships between the values of EPDO(equivalent property damage only) and the traffic and geometric elements. The main results analyzed are the followings. First, 6 negative binomial models are developed, which are all significant at the 90% confidence level. Second, the values of ${\rho}^2$ by vehicle type are 0.14307(auto), 0.35556(large van), 0.21684(small van), 0.205152(motocycle), 0.32338(light-duty truck) and 0.29046(heavy-duty truck), that are all analyzed to be statistically significant. Finally, the common variable included in all models is ADT(average daily traffic), and the specific variable(SV) of auto is analyzed to be the sum of lane width of main road, SV of large van is the average yellow time, and SV of small van is the difference in the number of lane between main and minor road.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.153-165
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• 2017

PURPOSES : With the increasing number of older drivers in an aging society, there is a growing need for research and planning on traffic safety for the older drivers using an improved road geometry design. This study also proposed a modified urban road interchange design, which aims to keep the older drivers away from accident-prone and high-traffic areas of the city. METHODS : In this study, we examined accident data records of older drivers to identify accident-prone zones and intersections; we studied the road geometry at these zones and analyzed if it was an underlying cause for higher number of accidents. Based on the research and subsequent analysis, we suggested plans for improvement of road geometry design at these intersections. RESULTS :By studying historic data and analyzing factors that affect the likelihood of accidents of vehicles driven by older drivers and after studying suitable traffic accident prediction models, we identified the major variables that need to be modified at accident-prone intersections, such as the width of a left turn lane at an intersection and the radius of the right turn lane at a street corner. The results have a significance probability of less than 0.001 and a 95% confidence level. To improve safety at the identified intersection, this study suggests the installation of a left-turn-lane-shaped Positive Offset and a right-turn-lane-shaped Slip Lane concept and an adjustment of intervals between intersections.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.167-175
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• 2020

In this paper, we propose a traffic accident detection on vehicle-mounted camera. In the proposed method, the minimum bounding box coordinates the central coordinates on the bird's eye view and motion vectors of each vehicle object, and ego-motions of the vehicle equipped with dash-cam are extracted from the dash-cam video. By using extracted 4 kinds features as the input of Bi-LSTM (bidirectional LSTM), the accident probability (score) is predicted. To investigate the effect of each input feature on the probability of an accident, we analyze the performance of the detection the case of using a single feature input and the case of using a combination of features as input, respectively. And in these two cases, different detection models are defined and used. Bi-LSTM is used as a cascade, especially when a combination of the features is used as input. The proposed method shows 76.1% precision and 75.6% recall, which is superior to our previous work.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.321-331
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• 2017

The objective of this study is to analyze the factors affecting the pedestrian accidents of roundabout near schools. To this end, this study has focus on the comparative analysis of pedestrian accidents across different school areas. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. To develop the pedestrian accident rate model, the linear regression model has been utilized in this study. 28 explanatory variables such as geometry and traffic volume factors are used. The main results are summarized as follows. First, the null hypotheses that the number of pedestrian accidents are the same are rejected. Second, 5 multiple linear regression accident models with higher statistical significance (adjusted $R^2$ of 0.651~0.788) have been developed. Third, while the common variables of 3 models (model I~III) related to school location are evaluated to be the pedestrian island, crosswalk, types of roundabout, elementary school and bus stop. Fourth, while the common variable of 3 models (model III~V) related to near school area or not is evaluated to be pedestrian island, type of roundabout, sidewalk, elementary school, speed hump, speed limit sign and number of entry lane. As a result, the installation of pedestrian islands and crosswalk might be expected to decrease the number of pedestrian accidents near schools.