• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.28-38
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• 2017

The study is to analyze the aggressive driving behavior in the protected/permissive left turn(PPLT) intersections in Gunsan City. As a result of the logistic regression model, increasing of driver's age and driving experience, non-peak time, no company, sedan and male have a tendency to behave aggressive driving to the opposite vehicles. When the vehicles try to turn the unprotected left in the PPLT intersection, the opposite vehicle drivers recognize them at the aggressive driving behavior if the distance to opposite vehicles is not enough. The relationship between driver characteristics and the distance to the opposite vehicles is analyzed under aggressive driving behavior. increasing of age and company, peak time tend to influence the short distance opposite vehicles while male and higher driving experience the middle and long distance. Sedan has the aggressive possibility to shorter distance opposite vehicles rather than others.

• 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.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.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.93-99
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• 2012

This study analyzes traffic data which are collected by VDS(Vehicle Detection System) to research the relationship between spacing distribution and vehicles' relative speed. The collected data are relative speed between preceding and following vehicles, passing time and speed. They are also classified by lane and direction. For the result of the analysis, in the same platoon, we figure out that mean of spacing is 40m, which can be a value to determine section A to D. To compare spacing according to time interval, this study splits time intervals to peak hour and non-peak hour by peak hour traffic volume. In conclusion, vehicles in peak hour are in car following because most drive similar speed as preceding vehicle and they have relatively small spacing. On the other hand, non-peak hour's spacing between vehicles is bigger than that of peak hour. This implies driver's behaviors that the less spacing, the more aggressive and want to reduce their travel time in peak hour, whereas most drive easily in non-peak hour and recreational trip purpose because of less time pressure.