• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.139-143
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• 2002

운전자가 고속도로와 시내도로에서 3시간 동안 주행했을 때 주관적인 운전 피로감 및 졸림감, 신체적인 불편도를 주관적 평가지를 이용하여 측정하였다. 실험결과 운전 피로감은 모든 주행조건에서 운전시간이 경과됨에 따라 유의하게 증가하였고 졸림감은 고속도로 주행시 운전시간에 따라 유의하게 증가하였으며 시내 주행에서 고속도로 주행보다 더 많은 신체부위에서 불편도가 높았다. 따라서 운전 피로는 운전시간에 따라 증가하고 고속도로에서는 졸음, 시내주행에서는 신체적인 불편으로 인한 피로가 증가함을 알 수 있었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.26-41
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• 2024

To ensure safer road conditions, understanding the human factors influencing driving behavior is crucial. However, there are many difficulties in deriving the characteristics of individual human factors that affect actual driving behaviors. Therefore, this study analyzes self-reported dangerous-driving propensities in order to explore potential correlations with drivers' behaviors. The goal is to propose a method for assessing driving tendencies based on varying traffic scenarios. The study employed a questionnaire to gauge participants' propensity to drive dangerously, utilizing a simulator to analyze their driving behaviors. The aim is to determine any notable connections between dangerous-driving propensity and specific driving behaviors. Results indicate that individuals exhibiting a high propensity for reckless driving, as identified by the Korean DBQ, tend to drive at higher speeds and display more aggressive acceleration patterns. These findings contribute to a potential method for assessing reckless driving drivers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.264-279
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• 2021

Most automated vehicle evaluation scenarios are developed based on the typical driving situations that automated vehicles will face. However, various situations occur during actual driving, and sometimes complex judgments are required. This study is to define a situation that requires complex judgment for safer driving of an automated vehicle as a dilemma situation, and to suggest a driving strategy necessary to secure driving safety in each situation. To this end, we defined dilemma situations based on the automated vehicle ethics guidelines, the criteria for recognition of error rate in automobile accidents, and suggestions from the automated vehicle developers. In addition, in the defined dilemma situations, the factors affecting movement for establishing driving strategies were explored, and the priorities of factors affecting driving according to the Road Traffic Act and driving strategies were derived accordingly.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.202-217
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• 2021

Following the fatal accident of pedestrians caused by Autonomous Vehicle by Uber, the world's largest ride-hailing company, two people were killed in a self-driving car accident by Tesla in April. There is a need to ensure the safety of road users. Accordingly, in order to secure the safety of Autonomous Vehicle driving, it is necessary to evaluate Autonomous Vehicle driving technologies in various situations based on the road and traffic environment in which the Autonomous vehicle will actually drive. Therefore, this study used UC-win/Road ver.14.0 based on general driver's license test questions to present a virtual reality-based Autonomous Vehicles driving ability evaluation tool among various driving ability test method. Based on this, it was intended to test driving ability for unexpected situations in complex and diverse driving environments, and to confirm its practical applicability as an optimal tool for Autonomous vehicle ability test and evaluation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.147-159
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• 2023

In order to make autonomous vehicles more trustworthy, it is necessary to focus on the users of autonomous vehicles. By evaluating the preferences for driving behaviors of autonomous vehicles, we aim to identify driving behaviors that increase the acceptance of users in autonomous vehicles. We implemented two driving behaviors, aggressive and cautious, in a driving simulator and allowed users to experience them. Biometric data was collected during the ride, and pre- and post-riding surveys were conducted. Subjects were categorized into two groups based on their driving habits and analyzed against the collected biometric data. Both aggressive and cautious driving subjects preferred the cautious driving behavior of autonomous vehicles.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.65-70
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• 2002

본 연구에서는 3시간 연속 운전에 따른 운전자의 피로감 및 생리적 반응을 고속도로 주행과 시내주행으로 실시하여 비교 검토하였다. 중추신경계 반응의 측정결과 양 주행조건 모두 각성되고 불쾌하였으나 시내주행의 경우가 상대적으로 각성되고 쾌한 경우가 많았던 것으로 나타났다. 한편, 시내주행의 경우는 심박수의 변화가 심하였으나, 고속도로의 주행에서는 눈깜빡임율이 크게 증가하였다. 따라서 2가지 주행 조건 모두 운전시간이 경과함에 따라 피로감을 느끼나 그러한 피로감을 느끼는 원인이나 현상은 상이한 것으로 나타났다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.7-10
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• 2012

본 논문에서는 스마트폰을 이용하여 도로 주행 정보를 기록하고 운전자에게 패턴 별 주행정보를 제공하는 라이프로그(Lifelog) 형태의 서비스에 목적을 두고 있다. 운전자의 도로 주행 데이터를 데이터베이스화한 이 정보는 다양하게 이용될 수 있다. 주행 패턴 인식은 이벤트 구간 검출 과정을 통한 패턴 구간을 검출하고 가속도 센서와 방향 센서, 즉 멀티 센서 기반으로 주행패턴을 인식한다. 주행 패턴을 분석 후 시간 정보를 이용하여 촬영된 영상 데이터에서의 패턴 구간 영상을 같이 제공한다. 이렇게 패턴 구간의 센서 스트리밍 정보와 영상을 제공하면 운전자의 운전 성향 및 주행 기록을 분석하는데 이용될 수 있다. 따라서 주행패턴 인식 알고리즘을 프로토타입으로 제안한다.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.61-74
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• 2005

This study is to investigate the effects of driving anger and traffic congestion on drivers' behaviors. Driving anger is the propensity to become angry while driving, and people differ in the tendency to get angry when encountering frustration and provocation on the road. Individual differences of the propensity contribute to anger on the road and aggressive driving leading traffic vaiolations and accidents. In the experiment three traffic conditions (an open road condition, a bumper-to-bumper traffic condition and a being stuck behind a slower driver condition) were simulated and driving behaviors were collected with RTSA-DS(Road Traffic Safety Authority-Driving Simulator). The results were as follows: Most of high anger drives drove at higher speeds in an open road condition, and in the bumper-to-bumper condition they drove faster and had an higher crash rate, which suggests they did aggressive driving, and risky and unsafe behaviors.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.169-183
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• 2018

Aggressive driving leads to a greater crash potential because it threatens surrounding vehicles. This study conducted traffic simulation experiments using driving behavior data obtained from multi-agent driving simulations. VISSIM traffic simulator and surrogate safety assessment model (SSAM) were used to identify the impacts of aggressive driving on traffic stream in terms of safety and operational efficiency. Market penetration rates (MPR) of aggressive driving vehicle, coupled with various traffic conditions, were taken into consideration in analyzing the impacts. As expected, it was identified that aggressive driving vehicles tended to deteriorate the traffic safety performance. From the perspective of operational efficiency, interesting results were observable. Under level of service (LOS) A, B, and C, it was observed that the average travel speed increased with greater MPRs. Conversely, the average travel speed decreased with under LOS D and E conditions. The outcome of this study would be effectively used for developing safety-related policies for reducing aggressive driving behavior.