• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.103-111
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• 2011

To evaluate highway safety countermeasures or identify high risk sites, the expected crashes for a site (or segment) have been estimated using the panel crash data. Past studies show that two different methods can be employed to estimate the expected crashes: observed crash based method and empirical Bayes (EB) method. This study conducts a simulation study to analyze how the estimation errors of the two estimates are affected by the different structures of the panel crash data and the presence of the change in safety over time. The results disclose that the estimation errors of the observed crash based estimates (i.e. the mean observed crash and comparative parallel estimate) are always greater than those of the EB estimates regardless of the structure of the panel crash data and the presence of the change in safety over time. Thus, it is highly recommended that the EB method be used in the study of traffic safety to obtain more reliable estimates for the expected crashes. In addition, this study corroborates that the estimation errors of the two estimates decrease as the analysis periods increase if safety does not change over time. Hence, it is also recommended that the 1-year analysis period used for identifying high risk sites in Korea be extended to produce more efficient estimates of the time-constant expected crashes.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.49-56
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• 2011

Understanding various casual factors affecting the occurrence of freeway traffic crash is a backbone of deriving effective countermeasures. The first step toward understanding such factors is to identify crash risks on freeways. Unlike existing studies, this study focused on the unsafe vehicle maneuvering that can be detected by in-vehicle sensors. The recent advancement of sensor technologies allows us to gather and analyze detailed microscopic events leading to crash occurrence such as the abrupt change in acceleration. This study used an accelerometer to capture the unsafe events. A set of candidate variables representing unsafe events were derived from analyzing acceleration data obtained by the accelerometer. Then, the crash risk was modeled by the binary logistic regression technique. The probabilistic outcome of crash risk can be provided by the proposed model. An application of the methodology assessing crash risk was presented, and further research items for the successful field implementation were also discussed.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.87-96
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• 2012

This research overcomes limit of prevention of disasters connection manual that was stopping in existing administrative formality presentation, and allowed purpose in substantial prevention of disasters countermeasure presentation through powerful engineering access. Did operation plan manual Tuesday in contiguity crossing that can reduce confusion by vehicleses that detour by contiguity IC of disaster point to do unusualness ashes in freeway section for this and solve jam-up phenomenon that occur by processing way insufficiency for roundabout way vehicles when happen. Metropolitan areas to target type classification in the highway along the highway adjacent to the intersection at Main Line Blocking optimum operating point analysis and an analysis of countermeasures in case of disaster, the lower the road entering the highway depending on the type of operating at the intersection were different. Depending on the results of analysis, while each point of a disaster, according to the characteristics of geometric conditions, traffic conditions, identify and determine the operating room and the adjacent intersection of media, and building systems to promote the driver if the quick initial response from the impending disaster situations and the safety of drivers can be considered secure.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.7-16
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• 2009

Provision of advanced warning information is one of the useful countermeasures to prevent traffic accidents. Analysis of user's preference for any information contents would be a backbone in designing more effective warning information systems. This study aimed at deriving more comprehensive and valuable warning information that leads to user's safer driving by conducting a questionnaire survey. In total, 258 people including various age groups and driving experiences participated in the survey. Preferable warning information contents were identified by this study. It is expected that the results would be useful data for providing warning information to drivers.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.145-151
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• 2009

Current highway design standards is based on the safety under the free flow condition. The length of deceleration lane is also determined in terms of the deceleration distance which is necessary for the driers to adjust the vehicle speed from the speed limit on the main road to that on the exit ramp of the interchange. However, the queues are frequently developed on the deceleration, and the following vehicles to exit must decelerate on the main road. It may cause delay on the main road and traffic accidents. This study is to suggest a methodology to minimize such problems with the shock-wave theory. The queue length of exiting vehicles can be estimated by the design speeds, traffic volumes of main road and the exiting ramp, and the countermeasures to the operational problems. According to the results, the queue length can be shortened to 80% by upgrading the design speed of exit ramp as the amount of 10km/h. Fifty percent of queue length can be shortened by adding an additional lane on the ramp to two lanes.

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

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

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.73-84
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• 2010

This study presents a novel method to identify hazardous segments of freeway using global positioning system(GPS) based probe vehicle data. A variety of candidate contributing factors leading to higher potential of accident occurrence were extracted from the probe vehicle dataset. The research problem was defined as a classification problem, then a well-known classifier, bayesian neural network was adopted to solve the problem. A binary logistic regression technique was also used for selecting salient input variables. Test results showed that the proposed method is promising in extracting hazardous freeway sections. The outcome of this study will be effectively used for evaluating the safety of freeway sections and deriving countermeasures to prevent accidents.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.136-143
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• 2015

Snow-melting system has been applied not only to roads for car traffic but also to pavement for the pedestrians safety reason in some of the developed countries such as USA and Canada based on countermeasures against Natural Disasters Act revised in 2000. Even though this system was introduced in korea in 2006 and has been partly applied to car traffic roads, there is few places that the system has been applied. Therefore, in this research a snow-melting system with a block-type to cover a pavement that efficiently transfers heat form heat rays to the top of a pavement and protects the heat rays. A quality check showed that compression and bending strength was improved approximately 5 times stronger and 7 to 10 times more absorption rate than the KS(Korea Industrial Standard) requirement. Moreover, only 10 minute was required to increase temperature above zero with a block-type snow-melting system whereas approximately 180 minute was spent with the existing system. This research is expected to contribute to environmental issues and reduce accidents on a slippery road.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.