• Journal of Environmental Science International
• /
• v.9 no.6
• /
• pp.469-474
• /
• 2000

The traffic accidents in large cities such as Pusan metropolitan city have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. In addition to the carelessness of drivers, many meteorological factors have a great influence on the traffic accidents. Especially, the number of traffic accidents is governed by precipitation, visibility, cloud amounts temperature, etc. In this study, we have analyzed various data of meteorological factors from 1992 to 1997 and determined the standardized values for contributing to each traffic accident. Using the relationship between meteorological factors(visibility, precipitation, relative humidity and cloud amounts) and the total automobile mishaps, and experimental prediction formula for their traffic accident rates was seasonally obtained at Pusan city in 1997. Therefore, these prediction formulas at each meteorological factor may by used to predict the seasonal traffic accident numbers and contributed to estimate the variation of its value according to the weather condition it Pusan city.

• International Journal of Highway Engineering
• /
• v.17 no.6
• /
• pp.85-95
• /
• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

• Journal of the Korean Society of Safety
• /
• v.33 no.3
• /
• pp.77-82
• /
• 2018

This paper aims to analyze the accident based on changing patterns of traffic culture index. For this purpose, this paper particularly focuses on classifying the traffic culture patterns and developing the traffic accidents using panel count data model. The main results are as follows. First, the traffic culture patterns are divided into 'increasing', 'decreasing' and 'other' patterns. The null hypotheses that the number of accident are the same over patterns are rejected. Second, 4 fixed effect negative binomial models which are all statistically significant are developed. Third, the regions with 'increasing' pattern are analyzed to be mostly the counties, and to demand the traffic law enforcement. Fourth, the regions with 'decreasing' pattern are evaluated to be mainly the districts and to require such the traffic culture as turn signal usage. Finally, the regions with 'other' pattern are analyzed to be mostly the cities and to ask for enhancing the level of traffic culture.

• 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.

• Journal of the Korean Society of Safety
• /
• v.27 no.3
• /
• pp.141-146
• /
• 2012

This study deals with the accident model using panel data which are composed of time series data of 2005 through 2007 and cross sectional data of link sections in Cheongju. Panel data are repeatedly collected over time from the same sample. The purpose of the study is to develop the traffic accident model using the above panel data. In pursuing the above, this study gives particular attentions to deriving the optimal models among various models including TSCSREG (Time Series Cross Section Regression). The main results are as follows. First, 8 panel data models which explained the various effects of accidents were developed. Second, $R^2$ values of fixed effect models were analyzed to be higher than those of random effect models. Finally, such the variables as the sum of the number of crosswalk on intersections and sum of the number of intersections were analyzed to be positive to the accidents.

• Journal of Korean Society of Transportation
• /
• v.20 no.4
• /
• pp.163-175
• /
• 2002

Fatalities from traffic accidents constitute one of the major health issues as well as safety ones in Korea. It has been reported that traffic accident is affected by the combined effects of road. vehicle. and human factors. Over the past few decades, a number of studies have been conducted to find the impact of road geometric factors on traffic safety. The purpose of this study is to investigate the effect of road geometric factors on traffic safety on Korean expressways. Detailed geometric design data were available from Korea Highway Corporation. Five-year traffic accident data on Honam expressway were collected and analyzed. It was found that following geometric factors influence traffic safety on expressways : radius of curve, curve length, and length of straight section. Furthermore, the existence of I.C. turned out to have a significant impact on traffic safety level. Based on the data analysis several multiple regression forms that relate traffic accident frequencies and geometric factors on expressways are developed.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.2
• /
• pp.54-63
• /
• 2023

Pedestrian traffic needs to be accurately quantified to predict effectively pedestrian traffic accidents, however, pedestrian traffic is more difficult to measure than vehicle traffic. In this study, we suggest the time-and cost-effective application of mobile closed-circuit television (CCTV) using a smartphone as an alternative that can collect and analyze real-time data with little. In the present investigation, the pedestrian-vehicle conflict that can develop into an accident was defined as the pedestrian accident exposure. After installing mobile CCTV in 40 sections of Dongseong-ro, Daegu, the pedestrian accident exposure was estimated through negative binomial regression analysis using the collected data. The results of the analysis showed statistically significant changes in the pedestrian accident exposure variables. Based on the present results, a pedestrian accident exposure estimation model was developed which can be used in sections where pedestrian accidents may occur.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.1
• /
• pp.111-117
• /
• 2017

The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.10
• /
• pp.995-999
• /
• 2010

Every year, traffic accidents and traffic congestion have been rapidly increasing, Although the roadway design and signal system have been improved to relieve traffic accidents, traffic casualties and property damage do not decrease. This paper develops a real-time traffic accident detection and analysis system (RTADAS): In the proposed system, we aim to precisely detect traffic accidents at different design and flow of intersections, However, because the data collected from intersections have uncertainty and complicated causal dependency between them, we construct probability-based networks for correct accident detection.

• Journal of Korean Society of Transportation
• /
• v.27 no.5
• /
• pp.97-111
• /
• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.