• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.16-30
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• 2019

In this study, we calculated the driving duration of individual vehicles according to the availability of rest facility on highway, and suggested indicators indicating the potential risk of accidents caused by long-term driving with weights based on the number of vehicles by driving duration of individual links. Based on this, the methodology for estimating the appropriate location of the highway rest facility considering the driving duration of individual vehicles was presented. Using the DSRC individual vehicle data collected from the highways, the appropriate location of the rest facility was calculated by considering the driving duration by classifying weekdays and weekends for the Gyeongbu Expressway. The results showed that the weekly and weekend high risk indicators were different. In the case of weekdays, the risk indicators of Gimchun JC to Kumho JC for Busan were high, while for weekends, the risk indicators of Ansung JC to Dongtan JC for Seoul and Ansung IC to Bukchunan IC for Busan were high. This study has great significance in that it provides a framework for detailed analysis of link units by using non-aggregated data of individual vehicle units. In addition, it is significant that the reasonable driving duration reflecting the behavior of individual vehicles was calculated by analyzing the use of rest facilities.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.1-14
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• 2012

Traffic management centers (TMC) collect real-time traffic data from the field and have powerful databases for analysing, recording, and archiving the data. Recent advanced sensor and communication technologies have been widely applied to intelligent transportation systems (ITS). Regarding sensors, various in-vehicle sensors, in addition to global positioning system (GPS) receiver, are capable of providing high resolution data representing vehicle maneuverings. Regarding communication technologies, advanced wireless communication technologies including vehicle-to-vehicle (V2V) and vehicle-to-vehicle infrastructure (V2I), which are generally referred to as V2X, have been widely used for traffic information and operations (references). The V2X environment considers the transportation system as a network in which each element, such as the vehicles, infrastructure, and drivers, communicates and reacts systematically to acquire information without any time and/or place restrictions. This study is motivated by needs of exploiting aforementioned cutting-edge technologies for developing smarter transportation services. The proposed system has been implemented in the field and discussed in this study. The proposed system is expected to be used effectively to support the development of various traffic information control strategies for the purpose of enhancing traffic safety on highways.

• Journal of Korean Society of Transportation
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• v.36 no.1
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• pp.51-65
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• 2018

Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of Digital Convergence
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• v.13 no.5
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• pp.289-296
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• 2015

This convergence study was conducted to compare difference of risk behaviors and injury incidence between younger(under 65 years) and elderly(over 65 years). For this analysis we used law data of nation-wide community health survey data during August to October 2010. Data of drink-driving, seat belt use, injury incidence rate, type of injury, cause of injury were used for comparison. Seat belt use(85.16% vs 78.81%) was high but drink-driving(12.99% vs 13.24%) was low in elderly. Injury incidence was high especially in falls(1.07% vs 2.22%). In conclusion, elderly do less risk behaviors, but experienced much more injuries especially falls.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.18-34
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• 2021

Pedestrian deaths in Korea due to traffic accidents are 40 percent of the fatalities in traffic accidents, which is about twice the average of OECD member countries. To reduce severe pedestrian accidents, it is necessary to apply the accident reduction measures to high-risk drivers (novice, elderly, and commercial vehicle drivers) who are more likely to cause traffic accidents than general drivers. Therefore, this study analyzed the effect of safe driving education on high-risk drivers' behavior. Here, the safe driving education is chosen as the measure to reduce traffic accidents. As part of the study, sudden pedestrian crossing situations were implemented in the driving simulator, and the vehicle trajectory data were collected to compare the driving behavior before and after the education. Most surrogate safety measures showed no improvement in the driving behavior of novice and elderly drivers, and the effect of safe driving education was found to be significant only in the group of commercial vehicle drivers. The results implied that additional measures such as pedestrian safety infrastructure and driver assistance systems, apart from the safe driving education, may be needed for novice and elderly drivers to reduce pedestrian accidents caused by them. With the findings mentioned above, this study is expected to provide a foundation to establish a plan to reduce pedestrian accidents caused by high-risk drivers.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.323-336
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• 2015

Estimating the risks on the roadway using surrogate safety measures (SSM) has an advantage in that it focuses on the vehicle trajectory directly involved in conflicts. On the other hand, there is a restriction on estimating the risks of continuous segments due to the limited data collected from a location. To overcome the restriction, this study presents the scheme of acquiring the vehicular trajectory using real time kinematics-differential global positioning system (RTK-DGPS) and develops a methodology which contains the considerations of the problems to calculate the SSM such as time-to-collision (TTC), deceleration rate to avoid collision (DRAC) and acceleration noise (AN). By using the methodology, this study shows a result from an experiment executed in a section where the variation of vehicular movement can be observed from several continuous flow roadway sections near Seoul and Gyeonggi Province in Korea. The result illustrated the risks on the roadway by the SSM metrics in certain situations like merging and diverging, stop-and-go, and weaving. This study would be applied to relate the dangers with characteristics of drivers and roadway sections, and prevenst accidents or conflicts by detecting dangerous roadway sections and drivers' behaviors. This study contributes to improving roadway safety and reducing car-accidents.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.312-318
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• 2017

This study calculated the cash flow using the financial information by fiscal year for 25 general hospitals and 23 hospitals, and analyzed the relationship between cash flow and net working capital. The analysis results showed that 73.3% of general hospitals and 83.3% of hospitals did not secure funds required for operating activities by fiscal year. The cash flow types that affect net working capital were expenses not involving cash outflows and changes in borrowings in general hospitals, and expenses not involving cash outflows and income not involving cash inflows and changes in borrowings in hospitals. However, in case of shortage of funds required for operating activities, at general hospital, due to expenses not involving cash outflows being high and income not involving cash inflows being low and resulting in increased borrowing, at hospital, due to expenses not involving cash outflows being high and resulting in increased borrowing. Therefore, for the stability of cash flow in management activities, the adequacy and relevance of the expenses not involving cash outflows need to be reviewed, and it will be necessary to review the appropriate internal policy measures to systematically and rationally manage cash flow in consideration of cash flows.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.