• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.32-45
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• 2018

This study aims to compare the mutual perception gap on dangerous driving behavior between male and female drivers in multiple aspects, analyze them, and identify factors that trigger this different perception. To understand the mutual perception gap on dangerous driving behavior, DBQ(Driving Behavior Questionnaire) was applied as a rating scale. By applying results into the Co-oreintation model, this study compared the mutual perception gap between male drivers and female drivers and analyze results. In addition, factors that generate the perception gap between both genders were drawn by analyzing factors. This study suggested that objective consistency identified the perception gap that driving behaviors of others were more dangerous between two genders. In addition, subjective consistency was different as both genders assumed that the counterpart's driving behavior takes more risks than their own actual driving behaviors. In regard to the accuracy, men were aware that female driving behaviors are more dangerous than their behaviors. However, female driving behavior assumed by women was consistent with male perception in all factors, which indicated that women perceive men precisely. In addition, results were compared and analyzed in both perspectives of male drivers and female drivers by combining predictive models. Based on these results, both genders perceived that counterpart's driving behavior is more dangerous among both genders.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.120-131
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• 2017

Recent studies have suggested that providing in-vehicle feedback on various driving behaviors promote eco-friendly driving behaviors. However, there was relatively little interest in cognitive overload that can be caused by the provision of information. Thus, the goal of this study was to investigate the relative effects of two types of feedback(visual feedback vs. visual-auditory feedback) to increase eco-driving performance while minimizing driving workload. Also, in this study, the complexity of the driving task was distinguished (secondary vs. tertiary task) in order to reflect the actual driving situation. The study adopted a counterbalancing design in which the two feedback types were delivered in a different order under the two different task conditions. Results showed that providing the visual-auditory feedback was more effective than the visual only feedback in both promoting eco-friendly driving behaviors and minimizing driving workload under both task conditions.

• 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.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.165-170
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• 2013

In this paper, we propose the information acquisition and analysis system for a vehicle driver in order to provide the safe driving environments. We first define the list of reckless driving behaviors and propose the recognition system, which recognizes the reckless behaviors, by using the acquired information. The collaboration among the information acquisition, the analysis, and the behavior comparison modules increases the accuracy of the recognition rate. Our system alarms to a vehicle driver in order to notify the potential to confront the dangerous situation due to the abnormal or reckless driving behaviors.

• Safety and Health at Work
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• v.13 no.2
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• pp.187-191
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• 2022

Background: Traffic injuries have become a significant public health problem in low- and middle-income countries. Several studies have examined the role of personality and attitude toward traffic safety in predicting driving behaviors in diverse types of drivers. Few studies have investigated risky behavior among public passenger van drivers. This study aims to identify the predictors of self-reported risky driving behavior among public van drivers. Method: A total of 410 public van drivers were interviewed at terminal stations in Bangkok. Hierarchical regression models were applied to determine the effects of demographics, personality traits, and attitude on self-reported risky driving behaviors. Results: The results indicated that drivers with a high education level, more working days, and high scores for normlessness and anger were more likely to report risky driving behaviors (p < 0.05). Conclusion: The personality traits and attitude toward speeding account for aberrant self-reported risky driving behavior in passenger van drivers. This could be another empirical basis for evidence-based road safety interventions in the context of public transport.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.499-510
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• 2015

The purpose of this research is to identify new service opportunities for enhancing driving safety of intra-city buses based on driving behavior analysis. Service opportunity identification involves finding target customers of service (to whom), motivations for service (why), service contents (what), and service delivery process (when, where). This paper presents an analysis of driving behaviors using the operational data of intra-city buses in conjunction with traffic accident data and drivers' driving history data. This paper also presents four identified service opportunities based on the data analysis results. This research would contribute to enhancing driving safety of intra-city buses in Korea and serve as a basis for developing new services for driving safety enhancement.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.199-209
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• 2015

This paper presents a model predictive control (MPC) approach to control the steering angle in an autonomous vehicle. In designing a highly automated driving control algorithm, one of the research issues is to cope with probable risky situations for enhancement of safety. While human drivers maneuver the vehicle, they determine the appropriate steering angle and acceleration based on the predictable trajectories of surrounding vehicles. Likewise, it is required that the automated driving control algorithm should determine the desired steering angle and acceleration with the consideration of not only the current states of surrounding vehicles but also their predictable behaviors. Then, in order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle during a finite time-horizon, we define a safe driving envelope with the consideration of probable risky behaviors among the predicted probable behaviors of surrounding vehicles over a finite prediction horizon. For the control of the vehicle while satisfying the safe driving envelope and system constraints over a finite prediction horizon, a MPC approach is used in this research. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope over a finite prediction horizon. Simulation and experimental tests show the effectiveness of the proposed algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.3
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• pp.119-127
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• 2020

The detection and recognition of abnormal driving becomes crucial for achieving safety in Intelligent Transportation Systems (ITS). This paper presents a feature extraction method based on spectral data to train a neural network model for driving behavior recognition. The proposed method uses a two stage signal processing approach to derive time-saving and efficient feature vectors. For the first stage, the feature vector set is obtained by calculating variances from each frequency bin containing the power spectrum data. The feature set is further reduced in the second stage where an intersection method is used to select more significant features that are finally applied for training a neural network model. A stream of live signals are fed to the trained model which recognizes the abnormal driving behaviors. The driving behaviors considered in this study are weaving, sudden braking and normal driving. The effectiveness of the proposed method is demonstrated by comparing with existing methods, which are Particle Swarm Optimization (PSO) and Convolution Neural Network (CNN). The experiments show that the proposed approach achieves satisfactory results with less computational complexity.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.17-40
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• 2002

The purpose of this study is to investigate the differences in the traffic environments and driving behaviors in 5 regions of Korea. Data were collected through the survey research from 1387 passenger car drivers in 14 locations in Korea. The main findings of this research are as followings: First of all, There were significant differences in traffic environment factors(road topography, construction, road & safety facilities, pedestrian behaviors, surrounding drivers) among 5 regional areas. When we examined drivers factors, there were significant differences among 5 metropolitan areas on wearing seat belt, most of constructions related to drink driving, speed-limit violation. There were many differences in driving habits, intentions, behaviors including wearing seat belt, driving after drinking according to metropolitan area, and also in case of speed-limit violation and careless driving behavior. These results suggested that there are many differences in traffic environments and driver's behaviors among regional areas. These result suggests that traffic safety policy and practice should be prepared based upon the peculiarities of regional area. We discussed these resulte in terms of the regional traffic policy and the suggestions for future studies were added.

• International Journal of Highway Engineering
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• v.20 no.4
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• pp.59-72
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• 2018

PURPOSES : This study was conducted to develop expressway safety treatments based on the analysis results of older driver behaviors through literature review, surveys, and driving simulator experiments. METHODS : In this study, three analyses were conducted: surveys of 700 older drivers to find the risk segments they recognized, driving simulator experiments with older and younger drivers to investigate driver behaviors, and expert surveys to find the priority of expressway safety treatments for older drivers. RESULTS : Through survey results it was found that merging areas and tunnels were identified as the most dangerous areas, and more dangerous older driver behaviors were observed on those expressway segments in the driving simulator experiments. In addition, the priorities of safety treatments for each segment of expressways were decided based on expert surveys. CONCLUSIONS : It was concluded that choice and concentration strategies of expressway safety treatments for older drivers should be applied as perceptions regarding dangerous spots and older driver behaviors, including geometric designs, safety facilities, regulation, and institutes to improve expressway safety.