• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.50-62
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• 2014

The number of traffic accidents has been decreased since 2000; however, the downward trend of crash occurrence has been slower after 2006. A few decades ago, physical improvement projects such as alignment improvement and the installation of safety facilities were usually implemented to decrease the occurrence of traffic accidents, but the effects of physical improvement on safety have been gradually decreased. The main objective of this study is to identify how the drivers' characteristics affect and/or are related to traffic accidents. Most of previous works have focused on revealing the difference of the nature of the drivers between the drivers who have no experience and the drivers with experience of traffic accidents. This study tries to analyze the habitual accidents proneness through a survey of drivers' personalities for drivers who were involved in traffic accidents at least once. As a result, nine personality factors were found to be statistically significant: Neuroticism(N), Lie(L), Psychoticism* Neuroticism(PN), Psychoticism*Lie(PL), Extraversion*Lie(EL), Neuroticism*Lie(NL), Impulsiveness(IMP), Venturesomeness(VEN), Empathy(EMP). Among these factors, single character factors were found to increase accidents, whereas complex factors were found to decrease the occurrence of accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.1-15
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• 2016

This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1591-1601
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• 2013

In this study, It is conducted for novice drivers about driving behavior and psychological characteristics analysis to reduce traffic accident risk and provide the basic data of education program development. Therefore, this study classified by the category-specific characteristics and hazard prediction through survey of the novice driver and unpredictable behavior and psychological characteristics were studied. The novice and general characteristics and driving behavior with vehicle simulators, comparison and analysis of the novice driver traffic safety education basic research direction based on the statistical results. Prediction the results of this study, the Hazard of the driver, speeding, traffic violation, information providing omission, abrupt change, the number of accidents in all areas novice driver is high compared to the general driver. In addition, Novice driver showed a statistically significant level of Hazard compared to the general driver target novice drivers and the general ability to predict Hazard of violation, abrupt change, and a number of traffic accidents were omitted level of speeding and other information providing level drivers all showed similar results. Vehicle simulator. The experimental results showed that novice drivers compared to drivers poorly overall driving performance. It showed a notable difference in the number of collisions, especially novice drivers compared to drivers in complex road traffic conditions due to a lack of driving experience and learning ability are considered.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.112-123
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• 2012

Different from general roads, intersections are the points where roads having different geometric structure and traffic operation system are met, and thereby they have complicated road structure and environmental factors. Various changes in driving patterns such as collision between vehicles approaching from roads adjacent to intersections, sudden stop of vehicles upon stop sign, quick start upon green lights kept increasing traffic accidents. It is known that traffic accidents are mainly derived from human factors. This study, in order to find out factors affecting drivers' behaviors within intersections, measured physiological responses such as brain wave, sight, driving speed, and so on by using state-of-the-art measuring device. As to concentration brain wave at individual intersections, it was found out that brain wave of testes was higher at main Arterial and accident-prone intersections compared with that of subsidiary Arterial. In addition, it was detected that drivers' visual activity was widely distributed at accident-prone intersections, meaning that it enhanced cautious driving from nearby vehicles. As to major factors causing drivers' workloads, factors from nearby vehicles such as deceleration, acceleration, lane change of nearby vehicles appeared as direct factors causing drivers' workloads, clarifying that these factors were closely related to causes of traffic accidents at intersections. Results of this study are expected to be used as basic data for evaluation of safety at intersections in consideration of physiological response of drivers.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.17-25
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• 2009

This research analyzed the changes of drivers' visual workload with beta wave of bionic signals from brain's occipital lobe from entrance to exit section of the Yuksimnyeong tunnel which is 3.1km long in Daejeon-Tongyeong section of Jungbu expressway. There are 10 subjects who Participate our experiments and the results are as follows. First. the drivers' visual workload is higher about 41% in entrance section of the tunnel than 200m in advance of the section of the tunnel. Second, it is higher than 200m in advance of the section of the tunnel by 34.5% that the value of the drivers' visual workload who is driving in the tunnel. Third, as a result of analyzing the tunnel into 200m unit section, it is statistically different from other sections' at the 1.0km and 2.4km section from the entrance of the tunnel. If drivers sustain average visual workload for safe driving in very long tunnel, it's not desirable environment that drivers' visual workload goes under the average workload. Therefore, it would be the section where drivers who is driving in tunnel could cause a traffic accident.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.115-132
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• 2017

Differences in reaction time and accuracy were compared among driver groups of middle-, old-, and stroke old-age drivers using various reaction time tasks including simple reaction task, 2-choice task, 4-choice task with different stimuli eccentricity, search task, and moving target detection task. The results can be summarized as followings. First, although overall reaction time tended to be slowed with age and stroke, stroke old drivers showed significantly slower reaction time than the other driver groups when the stimuli were presented in a large eccentricity. Second, differences in reaction time for 2-choice task and moving target detection task seemed to be determined mainly by participants' simple reaction time. Third, the search task which required temporary retention of previously presented stimuli was found to be more sensitive in discriminating difference in reaction time between middle-age drivers and old-age drivers (including stroke old drivers). Fourth, reaction accuracy of old (and stroke old) drivers decreased when more stimuli alternatives were presented and temporary retention for stimuli was required. Altogether, memory demand in reaction time task can be sensitive to evaluate performance for different age groups, whereas size of useful field of view for brain stroke.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.29-39
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• 2020

Some drivers cannot meet the standards for a full driver's license and many countries allow them to drive a vehicle as long as they can satisfy certain conditions. Korea has mainly issued conditional driver's licenses to the disabled only after supplementary devices are attached either in the vehicle or in their bodies. However, it is becoming important to issue a conditional driver's license to other types of drivers, including the elderly as the population ages in the country. This study aims at improving the current practice of issuing conditional driver's licenses by benchmarking various types of conditional licenses in other countries. In particular, various conditions such as time, space, driving speed, road type, vehicle type, and specific individual conditions are compared. Issuing a conditional driver's license to various types of drivers should be beneficial, not only to elderly drivers but also to drivers who cannot live without a vehicle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.193-201
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• 2011

The provision of traffic information plays an important role in increasing social benefit not only by saving travel time for individuals but also by improving the efficiency of road operation. VMS(Variable Message Sign) helps on-wheel drivers easily understand the road situation, and also provides real-time traffic information to people on the streets. However, it has not been sufficiently studied on how traffic information based on VMS influences on the drivers' selection of route. This study investigated how drivers use VMS traffic information and how they are satisfied with it. Then, the model of drivers' route selection was specified with the types of traffic information and the expected travel time to examine the influence on the selection of drivers' route. The model was estimated and analyzed in three types according to the condition of detour roads, and the rate of route change and the degree of sensitivity was calculated from the estimation. The results of analysis are as follows. the $1^{st}$ type model showed the 10% of route change for the travel time saving of 5minutes, and the 81.6% of route change for the travel time saving of 20minutes. The $2^{nd}$ type led to the range of route change from 14.2% to 92.7% over the 5 through 20 minutes of travel time saving. The $3^{rd}$ model resulted in the 99.1% of route change. The sensitivity of route change showed the highest for the travel time saving of 11 minutes with the $1^{st}$ type model, 9 minutes with the $2^{nd}$ type model, and 5 minutes with the $3^{rd}$ type model respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.47-65
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• 2014

VMS(Variable Message Sign) helps drivers to choose their path to destinations on roadways. Some types of VMS often provide traffic information with clearly visible and comprehensible graphical route diagrams. Currently many diagramed types of VMS are installed on urban arterial and highways. This type of VMS surely enhances drivers' ability to comprehend traffic route information while they are driving on the roadway. Nevertheless, some of them are presented with so much information and design elements and they sometimes lead to decline of drivers' comprehensible level for traffic information. Drivers would fail to decide their preferable route in this state of information overflow. The purpose of this paper is to develop a drivers preference model for effective design principle including size and height of displaying font, and the amount of information in the route diagram considering driving speed, sex and age of the driver. This model is developed using structural equation modeling techniques. This model considers driver's emotional factor and, human factor and design component of route diagram. To collect data, we built driving simulator which is able to replicate real driving condition. 72 people who participated in the simulation were selected considering gender and age. The developed model showed that the amount of information, and visibility are more influential factors to the drivers' preference of the route diagram on VMS than design elements such as the shape and the font of the diagram.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.37-46
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• 2012

The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.