• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.223-231
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• 2020

Older drivers have an increased risk of accidents due to poor function, but they also develop self-regulation ability to check their own changes. Thus, information on whether the actual elderly driver responds to changes in driving ability and risk may provide a meaningful basis for the clinic and research of the elderly's driving ability assessment. Therefore, the purpose of this study is to provide basic data for the evaluation of elderly drivers by analyzing the driving risk self-perception characteristics in terms of driving behavior and function with Korean elderly drivers. A self-reporting assessment was conducted on 500 elderly drivers living in the community and the characteristics of driving risk perception were analyzed. As a result, it was confirmed that many elderly drivers are aware of the driving risk when their vision and hearing are impaired or when they find it difficult to adapt to changes in driving conditions. On the other hand, the characteristics of insensitive reactions to changes in medical health conditions, such as drug use or epilepsy, seizures, and loss of consciousness, were identified. The researcher hopes this study will contribute to the safety management of elderly drivers in Korea, where aging is accelerating.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.149-161
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• 2009

Electronic control systems of vehicle are rapidly developed to keep balance of a driver`s safety and the legal, social needs. The driver assistance systems are putted into practical use according to the cost drop in hardware and highly efficient sensor, etc. This study has developed a lane and vehicle detection program using CCD camera. The Risky Driving Analysis Program based on vision systems is developed by combining a risky driving detection algorithm formed in previous study with lane and vehicle detection program suggested in this study. Risky driving detection programs developed in this study with information coming from the vehicle moving data and lane data are useful in efficiently analyzing the cause and effect of risky driving behavior.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.100-111
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• 2015

After empirically investigating the vehicle accident risks by age groups, various programs and policies have been imposed to reduce the old's risks in other countries. In Korea, it is little known the risk level by age groups and no policy changes has been implemented even if the number of vehicle accidents occurred by the old has been rapidly rising while the total number of vehicle accidents has been decreasing. This study empirically investigates the vehicle accident risks by age groups and the results show that the old drivers over age 65 has the highest accident risk except for the young drivers below age 25. Thus, we emphasize the necessity of reinforcing the qualifications for reissuing the drive licence and programs for educating the old drivers in Korea which is facing the most rapid population aging in the world. On the other hand, various changes are needed reflecting the old drivers such as reforming the road signs, issuing a sticker and providing them incentives such that the old drivers use the public transportation instead of self-driving.

• 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.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.205-206
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• 2017

도로교통공단 교통사고 분석시스템(TAAS)에 따르면 2016년 기준 전체사고의 약 11%가 고령운전자 사고이며, 고령운전자 사고로 인한 사망자수는 759명에 달한다. 본 연구에서는 고령운전자의 신체적 특징을 감안하여 전기(65세~74세), 중기(75세~84세), 후기(85세 이후)로 나누고 로지스틱 회귀분석을 이용하여 고령운전자의 연령대별 사고특성과 사망사고에 영향을 미치는 요인을 파악하고 그 특성을 고려한 안전대책을 제시하고자 하였다. 분석결과 차량단독사고일 때 고령자 전 연령대에서 사고위험도가 높게 나타났으며, 도로이탈로 인한 사고인 경우 다른 사고요인에 비해 위험도가 높게 나타났다. 사고원인별로 살펴보면 안전운전의무 불이행, 중앙선침범으로 인한 사고인 경우가 높았으며, 기상상태별로 볼 때 전기고령자에서 중기, 후기 고령자로 갈수록 흐릴 때의 사고위험도가 높아지는 것으로 나타났다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.152-166
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• 2022

This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.42-54
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• 2011

This study presented an algorithm to detect zigzag driving maneuver that is highly associated with vehicle crash occurrence. In general, the zigzag driving results from the driver's inattention including drowsy driving and driving while intoxicated. Therefore, the technology to detect such unsafe driving maneuver will provide us with a valuable opportunity to prevent crash in the road. The proposed detection algorithm used angular velocity data obtained from a gyro sensor. Performance evaluations of the algorithm presented promising results for the actual implementation in practice. The outcome of this study can be used as novel information contents under the ubiquitous transportation systems environment.

• 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.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.17-28
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• 2009

To analyze the risk according to accident types by novice and experienced drivers, it is used the accidents data which occurred for 2 years(2005~2006) in Korea. It is defined that novice driver is a people who is not passed 1 year after getting a driving licence and experienced driver is a people who is passed 1 year in this study. It is used a risk model to compare and analyze about the risk between two groups. The risk model is developed to apply together two variables which is accidents frequency and severity. Then it is used a conceptual weight to find that proper rate between accident frequency and fatal accident frequency. It is found a weight($\omega=0.6$) to suitable value to apply a risk model. The results showed that collision with obstacles, angle collision($90^{\circ}$) types to novice driver group have bigger risk than experienced driver group.