• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.5
• /
• pp.1135-1146
• /
• 2015

This thesis aims to improve the safety of bicycle traffic for activating the use of bicycle, main means of non-powered and non-carbon transportation in order to cope with worldwide crisis such as climate change and energy depletion and to implement sustainable traffic system. In this regard, I analyzed the problem of bicycle roads currently installed and operated, and developed the bicycle accident forecasting model. Following are the processes for this. First, this study presented the current status of bicycle road in Korea as well as accident data, collect the data on bicycle traffic accidents generated throughout the country for recent 3 years (2009~2011) and analyzed the features of bicycle traffic accidents based on the data. Second, this study selected the variable affecting the number of bicycle accidents through accident feature analysis of bicycle accidents at Jeollanam-do, and developed accident forecast model using the multiple regression analysis of 'SPSS Statistics 21'. At this time, the number of accidents due to extension per road types (crossing, crosswalk, other single road) was used. To verify the accident forecast model deduced, this study used the data on bicycle accident generated in Gwangju, 2011, and compared the prediction value with actual number of accidents. As a result, it was found out that reliability of accident forecast model was secured through reconciling with actual number of cases except certain data. Third, this study carried out field survey on the bicycle road as well as questionnaire on satisfaction of bicycle road and use of bicycle for analysis of bicycle road problems, and presented safety improvement measures for the problems deduced as well as bicycle activation plans. This study is considered to serve as the fundamental data for planning and reorganizing of bicycle road in the future, and expected to improve safety of bicycle users and to promote activation of bicycle use as the means of transportation.

• Journal of Korean Society of Transportation
• /
• v.29 no.3
• /
• pp.103-114
• /
• 2011

In this study, we discuss a fatal accident severity model obtained from the analysis of 112 crash sites collected since 2000, and the resulting relationship between fatal accidents and roadway geometry design. From the 720 times computer simulations for improving driving safety, we then reached the following conclusions:. First, the result of cross and frequency-analyses on the car accident sites showed that 43.7% of the accidents occurred on the curved roads, 60.7% on the vertical curve section, 57.2% on the roadways with radius of curvature of 0 to 24m, 83.9% on the roads with superelevation of 0.1 to 2.0% and 49.1% on the one-way 2-lane roads; vehicle types involved are passenger vehicles (33.0%), trucks (20.5%) and buses (14.3%) in order of frequency. The results also show that the superelevation is the most influencing factor for the fatal accidents. Second, employing the Ordered Probit Model (OPM), we developed a severity model for fatal accidents being a function of on various road conditions so as to the damages can be predicted. The proposed model possibly assists the practitioners to predict dangerous roadway segments, and to take appropriate measures in advance. Third, computer simulation runs show that providing adequate superelevation on the segment where a fatal accident occurred could reduce similar fatal accidents by at least 85%. This result indicates that the regulations specified in the Rule for Road Structure and Facility Standard (description and guidelines) should be enhanced to include more specific requirement for providing the superelevation.

• International Journal of Highway Engineering
• /
• v.10 no.4
• /
• pp.53-63
• /
• 2008

Even though accident frequencies in roadway segments have been decreasing since 2000, there has been increasing the number of vehicle crashes at intersections. Due to this increase, safety problems at intersection recently started to be regarded as significant issues. The purpose of this study is to analyze the effects of road conditions, traffic operational conditions, and other influencing condition on intersection safety. Then a traffic accident frequency prediction model to evaluate the safety at intersections was developed based on the correlations between influencing factors and vehicle crashes. In this research, critically significant factors affecting vehicle crashes at rural four-legs signalized intersections were investigated. It was found that Poisson regression was the best fit method to developing a accident frequency modeling using the collected data in this study. Through this study, it was concluded that exclusive left turn lane, crosswalk, posted speed, lighting, angle, and ADT are significant influencing factors on the intersection safety.

• Journal of Digital Convergence
• /
• v.19 no.4
• /
• pp.25-31
• /
• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Journal of Korean Society of Transportation
• /
• v.28 no.2
• /
• pp.123-133
• /
• 2010

The national standards for the installation of pedestrian crosswalks prohibits installation of crosswalks within 200 meters of nearby overpasses, underpasses, or crosswalks. In case the exceptional installation is required, the feasibility study is to be thoroughly conducted by the local police agency. However, it is an undeniable fact that the specific installation standards for optimal types and locations of crosswalks are not yet to be established. This paper examines the development of traffic accident prediction model applicable to different types and locations of bus stops(type A and type B) at mid-block intersections. Furthermore, it develops the poisson regression model which sets the "number of traffic accidents" and "traffic accident severity" as dependent variables, while using "traffic volumes", "pedestrian traffic volumes" and "the distance between crosswalks and bus stops" as independent variables. According to the traffic accident prediction model applicable to the type A bus stop location, the traffic accident severity increases relative to the number of traffic volumes, the number of pedestrian traffic volumes, and the distance between crosswalks and bus stops. In case of the type B bus stop model, the further the bus stop is from crosswalks, the number of traffic accidents decreases while it increases when traffic volumes and pedestrian traffic volumes increase. Therefore, it is reasonable to state that the bus stop design which minimizes the traffic accidents is the type C design, which is the one in combination of type A and type B, and the optimal distance is found to be 65 meters. In case of the type A design and the type B design, the optimal distances are found to be within range 60~70meters.

• Journal of Korean Society of Transportation
• /
• v.32 no.4
• /
• pp.369-379
• /
• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.47-54
• /
• 2006

In order to reduce traffic accidents, many researchers studied a traffic accident model. The Cause of traffic accidents is usually the mis calculation of traffic signals or bad traffic intersection design. Therefore, to analyse the cause of traffic accidents, it takes effort. This paper, it calculates the optimal safe car speed considering intersection conditions and weather conditions. It will recommend calculation of 1/3 in vehicle speed when there are rainy days and snow days. But the problem is that it will always display the same speed limit when whether conditions change. In order to solve these problems, in this paper, it is proposed the calculation of optimal safety speed algorithm uses weather conditions and road conditions. Computer simulations is prove that it computes the traffic speed limit correctly, which proposed considering intelligent traffic accident prediction algorithms.

• Journal of Korean Society of Transportation
• /
• v.30 no.6
• /
• pp.37-46
• /
• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.2
• /
• pp.397-405
• /
• 2015

In the past, expressways focused on mobility. However, the paradigm of expressways fuction today has been changed from fast expressways to safe expressways as people's quality of living and consciousness level heightened. In 2012, 3,550 traffic accidents occurred on expressways and 371 people died. The fatality rate of traffic accidents on expressways is almost twice that on general national roads. This study developed accident forecast models (safety performance functions) based on the number of traffic accidents and traffic volumes on six major lines on expressways. It is difficult to forecast safety performance functions for each expressway line because the lines and the scales of expressways are different from each other; therefore, integrated safety performance functions of six lines were determined first, and the coefficients, which can correct the traffic accidents on each line, were calculated. It is believed that this study will contribute in the safer management of expressways by being used as basic information in the establishment of traffic safety strategies for each expressway line in prevention of traffic accidents. Moreover, more studies would be required in the future, which would suggest reliable accident forecasts by calculating correction coefficients by line through integrated models by groups dependent on the characteristics of each line.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.107-116
• /
• 2002

Crash Cushion is a kind of safety facilities on roadside which acts the role of absorbing impact energy when vehicles are driven out of normal route such as Gore area of freeway off ramp. Criteria for severity index considering accident occurrence possibility are needed to have strong effect on installing the facilities. However, present criteria for establishing crash cushion design do not include such processes. Therefore, the paper presents two kinds of study to develop criteria for severity index. First of all, development of accident forecasting model on freeway off ramp is presented. The module is a relationship between accidents and road environment by negative binomial distribution (NB) which is called to reflect very well quality of accidents at Gore of crash cushion installed freeway Secondly, freeway exiting behavior model is developed because the human factor is the most important one. However, many literatures have shown between road environment and accidents which are more quantitative than human factor. The study supposed advanced process steps on actual freeway and analysed correlation between variables and accidents. The criteria for severity index is presented to determine whether to install or not by benefit cost analysis for each module. The standard for severity index will help to determine whether to install the crash cushion or not and to estimate severity for freeway and off ramp.