• International Journal of Highway Engineering
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• v.15 no.6
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• pp.113-123
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• 2013

PURPOSES : Although numerous researches have been studied to reveal accident causations for road intersections, there are still many research gaps for road segments. It is mainly because of difficulty of data and lack of analytical method. This study aims to study accident causations for rural road segments and develop accident modification factors for safety evaluation. The accident modification factors can be used to improve road safety. METHODS : Methods for developing AMF are diverse. This study developed AMFs using accident prediction models and selected explanatory variables from the accident models. In order to select final AMFs, three different methods were applied in the study. RESULTS : As a result of the study, many AMFs such as horizontal curves or vertical curves were developed and explained the meanings of the results. CONCLUSIONS : This study introduced meaningful methods for developing significant AMFs and also showed several AMFs. It is expected that traffic or road engineers will be able to use the AMFs to improve road segment safety.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.131-143
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• 2012

The past researches on roadway segment safety estimation focused on intersections, which are the primary traffic accident regions. The past researches on roadway segments, However, analyzed the effects of certain factors on the traffic accident occurrence rate by organizing the individual geometric structures of the roads, and there is still a dearth of researches on the development of a traffic accident estimation model for rural roadway segments. Therefore, this research focused on rural two-lane and multilane roadway segments and developed traffic accident estimation models through the application of statistical techniques. This is required to explain such high frequency of zero counts in the traffic accident data. In this research, it was found that the Hurdle model is more suitable than the Poisson or negative binomial-regression model for explaining the excess zeros case. In addition, main variables were chosen to estimate their effects on traffic accident occurrence at rural roadway segments, and the safety at such rural roadway segments was estimated. In this research, it was assumed that there are different factors that affect the safety at two-way lane and multilane roadway segments, and a traffic accident estimation model was developed by dividing the two-way lane and multilane roadway segments.

• 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.26 no.3
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• pp.67-74
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• 2008

Even though the efficiency of a point based black spot improvement project has been low, none of solid methodology, which is based on section not point, and is considered as one of the promising substitute, has not been come up with yet. Thus, this research aims at proposing the adequate length of a hazardous section and a method to set segment length over which the project needs to be performed on rural highways by analyzing the distances from project-conducted sites to new black spots in the following year and distances between project needed but not conducted sites and new black spots in the following year. According to the analysis, the probability of being a new black spot near the project conducted intersection is higher than that of a non-conducted intersection within 2km, however, no strong relationships between project types and distance distribution have been found. Based on those findings, a method to determine the target segment including adjacent black spots within 2 kilometers-range was proposed.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.145-150
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• 2014

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

• Journal of the Korean Institute of Rural Architecture
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• v.22 no.2
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• pp.1-8
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• 2020

This study is intended to derive the adaptive reuse techniques through the history and aspects of new construction, extension, repair, and other works, limited to the deep and narrow lots facing Seongan-gil and Nammun-gil in Nammun-ro 2 ga of Cheongju, the historic urban area. The results are as follows. 1) In the case of newly built reinforced concrete buildings, the central part of the top floor of the residence or all floors are opened to the open space(void) to facilitate lighting and ventilation. This is developed as a convection phenomenon due to the temperature difference from the slits between buildings, which affects the entire air flow of the block. 2) The buildings of extension and repair are composed of two-story masonry or steel frame, both the front store facing the road and the house on the back, but it looks like one because it is in contact with each other. If only a small gap between the front and rear buildings is restored to an external space or a space equipped with sun light, a small breath can be provided in lighting and ventilation. 3) The existing two-story wooden stores and houses have lost their external space due to repairs. With minimal intervention to restore the small courtyard, slits, and space under the eaves, it will not only improve lighting and ventilation, but also create a unique appearance as a segment of the elongated store.