• Journal of Communications and Networks
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• v.15 no.2
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• pp.173-178
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• 2013

It is a concern that eco-driving vehicles, because their driving behavior differs from other vehicles due to e.g. e-start, may inhibit smooth traffic flow. Therefore, it is necessary to study the cooperative eco-driving done by a vehicle group, putting "vehicle-to-vehicle communication" and "road-to-vehicle communication" into perspective. Based on these factors, this study aimed to: 1) Analyze fuel consumption rates and driving behaviors of more than one vehicle following an Eco-Driving vehicle. 2) Examine the effect of information on the fuel consumption rate of the preceding vehicles on the following vehicles. As a result, the following findings were obtained: 1) By providing information to multiple following vehicles, the fuel consumption rate of the second vehicle was not lowered, while that of the third one was. 2) It is possible that, when information on fuel consumption of a preceding vehicle is provided to the following one, an inter-vehicular distance is shortened during deceleration to contribute to smooth traffic flow. From the above results, it is suggested that, when targeting a vehicle group, sharing the information on preceding vehicles is effective.

• Knowledge Management Research
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• v.14 no.4
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• pp.47-74
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• 2013

Many organizations require employee's innovative behaviors, since one way for organizations to become more innovative is to capitalize on their employees' ability to innovate. However, employee's frequent conflict not only causes serious damage to organizations, but also blocks the authentic attitude of knowledge creation and has a negative impact on the innovative behaviors of employees. The purpose of this study is to examine the relationships among employee's task conflict and relationship conflict, employee's authentic attitude of knowledges creation, and innovative behaviors of employees in organizations. The result of analysis shows that the influence of task conflict on innovative behaviors is significant. And the influence of task conflict and relationship conflict on employees' authentic attitude of knowledge creation is significant. And the influence of employees' authentic attitude of knowledge creation on innovative behaviors is positively significant. Thus, the study provides researchers and practitioners with a matter of primary interest in knowledge creation as a driving force leading to innovative behaviors of employees, in which the authentic attitude of employees turns out to be an important psychological factor.

• Knowledge Management Research
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• v.14 no.5
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• pp.81-100
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• 2013

In this era of cut-throat competition, innovation is a source of competitive advantage, and securing core competency through innovation plays a pivotal role in ensuring the survival and growth of an organization. In an organization, R&D team is a core division driving innovation, and creative tension and conflict among researchers fuels innovative performance. Despite heated debate over the positive and negative effects of conflict, insufficiently-identified process factors have left sophisticated mechanisms between conflicts and effects unaddressed. This study assumes that team learning behaviors can bean important process factor given that conflict propels learning, and that learning is a decisive factor in creating competitive advantage. This study conducted an empirical analysis of the relationship between relationship/task conflict and team innovative performance, and the mediating role of team learning behaviors using data collected from a questionnaire sent out to the heads of 262 R&D teams and second highest-ranking officials thereof. The analysis conducted based on structural equation model indicates that relationship conflict has negatively affected team learning behaviors, whereas task conflict has positively influenced team learning behaviors(full mediation effect), team learning behaviors has positively influenced team innovative performance. Based on these results, the study has suggested implications of intra-team conflict and team learning behaviors for team innovative performance.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.6-13
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• 2024

This paper presents a method of longitudinal motion planning of autonomous vehicles to deal with the non-signalized crosswalk environment. Based on the traffic laws, vehicles should slow down when passing the non-signalized crosswalk to prepare for situations where a nearby pedestrian starts to cross. If a pedestrian is in the crossing phase, vehicles should stop in front of the stop-line and wait until the pedestrian finishes the crossing maneuver. To realize these behaviors in autonomous vehicles, the driving mode and corresponding driving strategy are determined when vehicles encounter the crosswalk. The driving mode is determined according to the behavioral status of the nearby pedestrian. Longitudinal motion for the stopping or passing maneuver is planned according to the determined driving mode. The proposed algorithm has been validated via autonomous driving tests with our test vehicle in a real world. The test results show that the proposed algorithm enables the test vehicle to follow the traffic laws and behave safely against crossing pedestrians in the non-signalized crosswalk.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.207-217
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• 2014

Many a number of policies have been tried to reduce auto accidents so far, but it is obvious that further studies are still needed to find a more fundamental and multi-dimensional preventive measure with effect. The National Mental Health Statistics shows that the most profound forms of negative emotions, that is, depression and anxiety, have been increasing, but studies on such a topic are scarce to find. Therefore, we conducted a structural analysis between the negative emotions, including depression and anxiety, of drivers and their driving behaviors using a Structural Equation Modeling(SEM) technique. The review of past literature and studies indicated that not all of human emotions manifest themselves as the ultimate behaviors because they go through emotion regulation Strategies. For this reason, the purpose of this study was set to analyze the structural model developed in this study reflecting the emotion regulation strategies. The result of our analysis showed that the driver's negative emotion had a more significant influence on dangerous driving behaviors than safe ones, and especially, the expressive suppression strategy was found to be the highest factor. Also, the total effect analysis with the negative emotional factors showed that expressive suppression had more significant influence compared to that of cognitive reappraisal. The implication of this study might provide a better understanding on driving behaviors of the drivers and could be used as a fundamental study for future policy development to reduce traffic accidents.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.26-33
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• 2009

The directions of the road are divided into two, the right-hand side and left-hand side of the road, by the convention and specific native method in the world. This paper deals with the characteristics and behaviors of drivers who are accustomed to driving on right-hand side of the road, drive with a handle on the left-hand side, and comparing with left-hand side drivers. The driver's eye movements were measured by eye camera and questionnaires were used for measuring subjective evaluation such as driving mental workload. The experimental results indicated even if the experts who had much experience on right-hand side driving, they had lower driving skill than novice driver, accustomed to driving on left-hand side. In terms of mental workload, MCH rating scale and MNASA-TLX, the right-hand side drivers were in lower stress condition than the left-hand side drivers because of having much driving experience. However, they conducted a few mistakes by confusing the position of turn signal and windshield wiper because of their driving habit or traits and it lead to operation mistakes. These results can be applied effectively to develop the driving support information with changed environments.

• Korean Journal of Culture and Social Issue
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• v.17 no.3
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• pp.305-320
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• 2011

The objectives of the present research are twofold. First, this research aims to compare the effect of trait characteristics(sensation seeking, social resistance and type-A behavior) with that of driving specific characteristics(driving anger and type-A driving) on problematic driving behavior. Second, the role of life stress as a mediator in the relationships between general trait characteristics and traffic safety index was examined. 1158 licensed commercial vehicle drivers were surveyed and their accident-related records were obtained in this research. Results showed that driving specific characteristics were significant indicators of traffic safety and life stress mediated the relationships between general trait characteristics and traffic safety index. These findings implicate that understanding drivers' driving specific characteristics and their levels of life stress is important to reduce problematic driving behaviors and enhance traffic safety.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.85-95
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle accidents explains 3.5 percent of the total number of traffic accidents of the year. Compared to other types of vehicles commercial vehicles may provide more serious damages to both driver himself and passengers. Thus, they generate more serious social and economic problems. There have been various forms of systems such as a digital speedometer or a black box to meet the social requirement for reducing traffic accidents and improving safe driving. However, since the current systems are based on the data often accidents happened, there are lots of limitations to control drivers in real-time. Also, the current speedometers provide drivers with only speeds of vehicles and RPM information regardless of actual dangerous drive behaviors. Therefor, they lack of the effectiveness in terms of safety. In this research, real-time information systems for improving driver safety based on automatic risky driving behaviors, and thresholds to determine risky driving patterns were studied.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.142-148
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• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.95-105
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• 2007

Speeding and drunken driving make drivers fail to detect hazards and cope with various driving situations. These behaviors also raise the possibility of being involved in traffic accidents and tend to increase the number of fatalities. The authors compared the driving behavior determinants of a rockless drivers group, consisting of individuals who have committed traffic accidents or offended regulations through drunken driving, with a normal drivers group. In the results, the reckless drivers group showed high scores of 'speeding' and 'drunken driving', and they also stated that they had more experiences of speeding, drunken driving and traffic accidents. In the path analysis study, it was found that the impacts of the rockless drivers group's 'risk sensitivity' and 'situational adaptability' on traffic accidents were stronger than those of normal drivers. This means 'risk sensitivity' and 'situational adaptability' can explain the origins of traffic accidents better in the reckless drivers group than accidents of the normal drivers group.