• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.64-75
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• 2017

Previous count models using fixed parameter can not consider the unobserved heterogeneity, as the standard error of the count value is underestimated, excessive t-values are derived thereby reducing the reliability of the model. Also, the study of unsignalized intersections are inadequate because of the difficulty of collecting data and statistical limits for accurate analytical processes compared to the signalized intersections. The purpose of this study is to analyze the factors affecting traffic accidents by constructing the count model using random parameters, and it aimed to distinguish between existing studies based on the rural unsignalized intersections. As a result of the analysis, 7 variables were presented as significant variables, and 2 variables(presence of crosswalk, speed limit) were presented as random parameter.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.60-75
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• 2019

Nowadays, interest in safety of pedestrians who are relatively weak when compared with vehicles increases. Also, concern for pedestrian accidents on crosswalks increases. For these reasons, scrambled crosswalks which are considered to contribute pedestrian safety by reducing conflicts between vehicles and pedestrians are actively discussed and there are also a few intersections where they are actually installed. However, scrambled crosswalks must include all-red phase for all vehicle traffic flows, which inevitably leads to increase of lost time per cycle. Therefore, evaluation in terms of efficiency should be done before installation of scrambled crosswalks. This research suggests installation criteria for scrambled crosswalks so that it is possible to judge whether installation of scrambled crosswalks is appropriate only by surveying vehicle traffic volume and pedestrian traffic volume. This research derives optimum cycle length from signal optimization models which considers both vehicle traffic volume and pedestrian traffic volume. From this optimum cycle length, this research compares total delay time before and after installation of scrambled crosswalks. From an analysis, two research results are derived. Firstly, there is critical traffic volume above which installation of scrambled crosswalks can not efficient. Secondly, appropriate areas for installation of scrambled crosswalks are different by each signal intersection or by each signal system and those difference vary. From these results, this research suggests installation criteria for scrambled crosswalks which consists of two steps. The delay time of the pedestrians may be increased after the diagonal crosswalk is installed, but it may be desirable to install in consideration of the appropriate traffic level to ensure safety.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.55-63
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• 2002

It has been known well that Traffic Conflict Technique(TCT) used to evaluate the safety of intersections in the case of shortage of traffic accidents data and surveying time. Because data for using in traffic conflict technique that is collected by trained surveyors, it is rely on the knowledge, experience and the characteristics of them. The data of surveying generate varying result. So, its variance must minimize and then it is considered of calculating in traffic conflict technique however obviously technique to minimize has not developed until now. So, this paper has a focus on the technical method to minimize the variance. For this, it applied the fuzzy reasoning theory to the existed traffic conflict technique that is the most comprehensive method in the country and then developed the new traffic conflict technique model. Fuzzy reasoning theory is a very appropriate method for minimizing the variance among surveyors because it can systematically calculate the uncertainty of surveyors by approximation reasoning structure. The result of analysis from pilot study, the new Procedure in this Paper minimized the variance by 53 Percentiles and it increased the value of conversion factor two times than the exited traffic conflict technique. The method proposed in this paper, it can be used for evaluating the safety of intersection, and before and after analysis of improving Project of black spots.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.11-18
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• 2022

The use of multi-spectral cameras is essential for day and night pedestrian detection. In this paper, a color camera and a thermal imaging infrared camera were used to detect pedestrians near a crosswalk for 24 hours at an intersection with a high risk of traffic accidents. For pedestrian detection, the YOLOv5 object detector was used, and the detection performance was improved by using color images and thermal images at the same time. The proposed system showed a high performance of 0.940 mAP in the day/night multi-spectral (color and thermal image) pedestrian dataset obtained from the actual crosswalk site.

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.554-563
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• 2015

This study dealt with developing an accident model for rural signalized intersections with random parameter negative binomial method. The limitation of previous count models(especially, Poisson/Negative Binomial model) is not to explain the integrated variations in terms of time and the distinctive characters a specific point/segment has. This drawback of the traditional count models results in the underestimation of the standard error(t-value inflation) of the derived coefficient and finally affects the low-reliability of the whole model. To solve this problem, this study improves the limitation of traditional count models by suggesting the use of random parameter which takes account of heterogeneity of each point/segment. Through the analyses, it was found that the increase of traffic flow and pedestrian facilities on minor streets had positive effects on the increase of traffic accidents. Left turning lanes and median on major streets reduced the number of accidents. The analysis results show that the random parameter modeling is an effective method for investigating the influence on traffic accident from road geometries. However, this study could not analyze the effects of sequential changes of driving conditions including geometries and safety facilities.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.266-279
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• 2014

For the evaluation of roadway safety, diverse methods, including before-after studies, simple comparison using historic traffic accident data, methods based on experts' opinion or literature, have been applied. Especially, many research efforts have developed traffic accident prediction models in order to identify critical elements causing accidents and evaluate the level of safety. A traffic accident prediction model must secure predictability and transferability. By acquiring the predictability, the model can increase the accuracy in predicting the frequency of accidents qualitatively and quantitatively. By guaranteeing the transferability, the model can be used for other locations with acceptable accuracy. To this end, traffic accident prediction models using non-linear regression, artificial neural network, and structural equation were developed in this study. The predictability and transferability of three models were compared using a model development data set collected from 90 signalized intersections and a model validation data set from other 33 signalized intersections based on mean absolute deviation and mean squared prediction error. As a result of the comparison using the model development data set, the artificial neural network showed the highest predictability. However, the non-linear regression model was found out to be most appropriate in the comparison using the model validation data set. Conclusively, the artificial neural network has a strong ability in representing the relationship between the frequency of traffic accidents and traffic and road design elements. However, the predictability of the artificial neural network significantly decreased when the artificial neural network was applied to a new data which was not used in the model developing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.59-66
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• 2010

Korea have experienced a very rapid increase in police-reported collisions between bicycle and motor vehicles over the past decade. Even though cycling accidents are increasing, efforts to make urban areas more accomodating to cyclists are seldom formed. Clearance intervals(including both the yellow change and all-red clearance intervals) at signalized intersections that are of inadequate lengths for bicycles may cause accidents. Data on bicycling speed, acceleration and deceleration were tested and analyzed on the flat. Using the results of the analysis and based on the AASHTO's equation of the bicycle clearance interval, a methodology is got for calculation safe clearance intervals for bicycle riders. The clearance interval call for bicycles will be larger or same than for vehicles because of the speed, acceleration and deceleration difference. Adequate bicycle speed, acceleration and deceleration for korean bicycle users is presented in this paper. It is hoped that traffic engineers to provide safe intersection clearance time for bicycles use the results of this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.58-69
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• 2002

Most of the traffic accidents are a rear-end collision and a clash generated in the signalized intersection on the local roads. So, it is demanded that the high-quality of signal control and dilemma zone control. According to the cases generated by foreign countries, we established the strategies which are composed of Volume-Density Control, strategy of the dilemma zone control using R-detector (microwave detector) In Japan and EC-DC Control. MOEs(Measure of effectiveness) are car numbers in the dilemma zone , max-out probability in the safe side and the average stopping delay in the progress side. We choose a signalized intersection in rural highway to analyze the effect of the strategies and practiced an on-the-spot survey. The result of the survey is applied to the basic data in the simulator. Consequently, strategy of the dilemma zone control using R-detector(microwave detector) in Japan is the best effective in the safe side and EC-DC control is the best in the progress side. Based on the result, we developed the effective strategy of the signal control . This strategy is composed of the strategy of Japan and the detector on the stopping line used in the EC-DC control. On the result of the analysis, new strategy is the best effective in two sides.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.