• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.15-28
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• 2008

According to the accident statistics published by the National Police Agency in 2006, it can be recognized that drivers' characteristics and driving behaviors are the most causational factors on the traffic accidents. At present, although many recording tools such as digital speedometer or black box are distributed in the market to meet social requests of decreasing traffic accidents and increasing safe driving behaviors, it is also true that it still lacks in obvious categories for dangerous driving types and then, the efficiency of the categories to be studied has been low. In this study, dangerous driving types are redefined. They are grouped into 7 classifications in the first level, and the seven classifications are regrouped into 16 in more detail. To verify the redefined dangerous driving types, a Data-logger is developed to receive and analyze the data that occur from the driving behaviors of the test vehicle. The developed Data-logger can be used to construct a real time warning system and safe driving management system with dangerous driving patterns based on acceleration, deceleration, Yaw rate, image data, etc.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.149-160
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• 2007

Automobile black boxes store and provide accident and driving information. The accident and driving information can be utilized to build scientific traffic-event database and can be applied in various industries. The objective of this study is to develop a recognition system of dangerous driving through analyzing the driving characteristic patterns. In this paper, possible dangerous driving models are classified into four models on the basis of vehicle behaviors(acceleration, deceleration, rotation) and accident types from existing statistical data. Dangerous driving data have been acquired through vehicle tests using automobile black boxes. Characteristics of driving patterns have been analyzed in order to classify dangerous driving models. For the recognition of dangerous driving, this study selected critical value of each dangerous driving model and developed the recognition algorithm of dangerous driving. The study has been verified by the application of recognition algorithm of dangerous driving and vehicle tests using automobile black boxes. The presented recognition methods of dangerous driving can be used for on-line/off-line management of drivers and vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.87-97
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• 2018

Bus, a major transportation mode, doesn't have a systematical evaluation system for dangerous driving behavior yet. This paper analyzes the characteristics and pattern of bus driving behavior using Digital Tacho Graph(DTG) data on express bus. 8 types of dangerous driving behavior were considered according to timeslot, the day of week and weather condition. As results, rapid acceleration, rapid left right turn and rapid deceleratio accounted for more than 97% and relatively high percentages were shown in dawn, on Friday and on the clear day, respectively. From the statistical analysis, correlation between the dangerous driving types and difference according the timeslot were found, and 3 groups considering the level of the dangerous driving were suggested. This study contributes to setting an efficient and reliable eduction system for using driving simulators.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.554-559
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• 2005

It seems to be dangerous to use a cellular phone while driving since it increases driver's mental stress and makes driver's reaction time slow. This study is to investigate driver's psycho-physiological responses on mobile telephoning while driving. Among the three experimental factors (mobile-phone types, message IODs over mobile-phone, road types), only the message IODs over mobile-phone changed R-R intervals of electrocardiograph significantly. This result suggests that the regulations on the mobile telephoning while driving be changed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.145-154
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• 1998

The effects of secondary task on driving performance and subjective workload were investigated during a simulated driving. The driving performance was determined by the appropriateness of break timing. The driving simulator was provided by the Korea Road Traffic Safety Association. The subjective workload was tested by using a multidimensional measure such as NASA-TLX. Road was categorized into two types: narrow alley and wide street. The secondary task included pushing the number on the cellular phone, pushing radio channel, and conversing with a passenger. Seventeen subjects volunteered in the study. The data were analyzed by using SAS. Results showed that using the cellular phone and pushing channel during driving caused 3∼22% decline of driving performance and 42∼59% increase of subjective workload respectively. These results indicated that the secondary task could be potentially dangerous although there was not a significant performance decrease due to the notable increase of mental workload. In the future, if we can use a more sensitive and realistic driving simulator, the effects of secondary task under a dynamic driving situation can be investigated.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.15-28
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• 2016

The purpose of this study is to prepare countermeasures for aggressive driving and road rage which have recently become a hot issue by analysing mechanism of how the driving behavior determinants(personal anger and aggression) and dangerous driving behavior factors(aggressive driving behavior and over-speeding driving behavior, drunk driving behavior, inattentive driving behavior, and inexperience driving behavior) affect aggressive driving and road rage. From the survey conducted by seven branches of the Road Traffic Authority with 351 people who were traffic offenders and drivers who caused car accidents, this study obtained three results as follows. First, seriousness of aggressive driving and road rage and requirements as types of customized educations, proper length of time for education, and contents of education can be understood. Second, specific relation and mechanism between the driving behavior determinants and dangerous driving behavior factors with respect to aggressive driving and road rage can be clearly identified, which helps to set order of priority and weighting of measures for reducing aggressive driving and road rage. Third, countermeasures can be categorized as corporate measures or customized measures through mechanism analysis model of aggressive driving and road rage.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.105-115
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle(city, suburb and other buses) accidents consumes 3.5 percent of the total number of traffic accidents in this year. Since the commercial vehicles are responsible for not only the drivers but also the passengers, it leads more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and safe driving. however the system based on the data after accident control the driver by analyze dangerous drive behaviors, so there is a limit to control driver in real-time. Also speedometer currently managed provide the driver warning information in real-time, but using only the speed of vehicle and RPM information regardless of actual dangerous drive behaviors, disappear the effectiveness. In this study performed a simulation for drivers in general using a simulator programed with dangerous driving types we had developed in the previous study and judging the types. It'd be more effective system to provide the drivers warning information using weight valued in this study. However in this study is limited to apply weight as a result of simulation of drivers in general in actual situation should be made up the deficit based on information of driving type of actual commercial vehicles.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.171-179
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• 2013

The primary function of navigation system is to provide route search and road guidance for safe driving for drivers. However, the existing route search system provides a simple service that looks up the shortest route using a safe driving DB without considering different road characteristics for the safety of the drivers. In order to maintain the safe driving, rather than searching the shortest path, a navigation system, in which the danger areas and/or the dangerous time zones have been considered, is required. Therefore, in this paper we propose a strategy of searching a navigation path to avoid danger areas for safe driving by using the A* algorithm. In the strategy, when evaluating the path-specific fitness of the navigation nodes, different heuristic weights were assigned to different types of risk areas. In particular, we considered three kinds of danger areas, such as accident-prone sections where accidents occur frequently, school zones, and intersection regions, as well as the time slots when the probability of danger is high. From computer simulation, the results demonstrate that the proposed scheme can provide the way to avoid danger areas on the route searching and confirm the possibility of providing the actual service.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.223-230
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• 2021

Currently, self-driving vehicles are on the verge of commercialization after testing. However, even though autonomous vehicles have not been fully commercialized, 81 accidents have occurred, and the driving method of vehicles to avoid accidents relies heavily on LiDAR. In order for the currently commercialized 3-level autonomous vehicle to develop into a 4-level autonomous vehicle, more information must be collected than previously collected information. Therefore, this paper proposes a Driving Situation Judgment System (DSJS) that accurately calculates the crisis situation the vehicle is in by useing the roughness of the road and the state of the passengers of surrounding vehicles including road information and weather information collected from existing autonomous vehicles. As a result of DSJS's PDM experiment, PDM was able to classify passengers 15.52% more accurately on average than the existing vehicle's passenger recognition system. This study can be a basic research to achieve the 4th level autonomous vehicle by collecting more various types than the data collected by the existing 3rd level autonomous vehicle.

• Korean Journal of Culture and Social Issue
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• v.19 no.3
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• pp.367-388
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• 2013

This study examined how drivers of different cultural orientations(individualism vs. collectivism) attribute the cause(dispositional vs. situational) of four simulated driving situations which were varied in types(cutting-in and sudden-stop by the other driver) and differential emphasis on other the other driver's driving attitude or situational factor. The results showed the followings. First, the drivers generally showed higher attribution scores on the dispositional factor than the situational factor, except for the 'sudden-stop: situation emphasis' scenario condition. Second, when drivers' cultural orientation and attribution styles were considered together, it was found that, except for the 'cutting-in: disposition emphasis' scenario condition. the drivers of collectivism tended to attribute more to situational factor than the drivers of individualism, In contrast, the drivers of individualism showed higher attribution scores on dispositional factor than situational factor in all driving scenario conditions. Implication and suggestion were discussed.