• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.69-80
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• 2002

차로변경이 발생하는 두 가지 상황 즉, 강제 차로 변경과 선택적 차로 변경 중, 선택적 차로변경 상황에서 운전자가 수락 가능한 간격을 발견했을 때, 차로별 속도 차가 차로 변경 의사결정에 미치는 영향을 모사할 수 있는 모형식을 추정하였다. 즉, 선택적 차로 변경은 운전자의 차로 변경 여부에 대한 상황판단과 함께 목적 차로의 간격 수락여부에 대한 의사결정으로 이루어지는데, 본 논문에서는 목적 차로에 수락 가능한 간격이 존재할 경우 차로별 속도차가 운전자의 의사결정에 어떤 영향을 미치는지에 대해 분석하였다. 이를 위해, 운전자 의 의사결정에 영향을 미칠 수 있는 다른 요소 즉, 중차량, 기하구조, 및 합·분류의 영향을 최소화하는 지점을 선택하여 표본조사를 실시하였으며, 보다 설명력 있는 모형식을 얻기 위해 상관분석 등을 수행하여 불필요하다고 생각되는 변수는 제외시켰다. 또한, 운전자의 희망속도와 주행 속도 차에 의한 영향을 반영하기 위해 현 차로 속도를 부가적인 변수로 추가하였으며, 계수추정은 통계패키지인 SAS를 이용하였는데, 자료분석에 있어, 속도차 구간에 따라 다른 간격수락 특성을 보여 차로별 속도차를 0∼2.0m/s구간과 2∼11.52m/s구간으로 나누어 분석을 수행하였다. 분석결과 속도차 0∼2.0m/s구간에서는 속도차가 증가할수록 차로 변경률이 높아졌으나, 2∼11.52m/s구간에서는 오히려 차로 변경률이 낮아지는 것으로 나타났는데, 이는 속도 차의 증감에 대해 운전자로 하여금 차로 변경을 유도하는 요소와 함께 저항하게 하는 요소가 있다는 것을 알 수 있었다. 분석결과. 2.0m/s 이상의 속도차에서 차로변경에 대한 저항이 상대적으로 크게 작용한다는 것을 알 수 있었으며, 도로 설계시 이를 반영하여 도로기하구조 및 안전성 등을 향상시킬 수 있을 것으로 보인다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.73-82
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• 2017

As of December 2016, the number of registered automobiles in Korea exceeds 21million. As a result, greenhouse gas emission by transportation sector are increasing every year. It was concluded that the development of the driving strategy considering the driving behavior and the road conditions, which are known to affect the fuel efficiency and the greenhouse gas emissions, could be the most effective fuel economy improvement. Therefore, this study aims to develop a fuel efficient driving strategy in a complex linear section with uphill and curved sections. The road topography was designed according to 'Rules about the Road Structure & Facilities Standards'. Various scenarios were selected. After generating the speed profile, it was applied to the Comprehensive Modal Emission Model and fuel consumption was calculated. The scenarios with the lowest fuel consumption were selected. After that, the fuel consumption of the manual driver's driving record and the selected optimal driving strategy were compared and analyzed for verification. As a result of the analysis, the developed optimal driving strategy reduces fuel consumption by 21.2% on average compared to driving by manual drivers.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.105-115
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• 2009

According to the accident statistics published by the National Police Agency in 2007, the number of commercial vehicle(city, suburb and other buses) accidents consumes 3.5 percent of the total number of traffic accidents in this year. Since the commercial vehicles are responsible for not only the drivers but also the passengers, it leads 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 safe driving. however the system based on the data after accident control the driver by analyze dangerous drive behaviors, so there is a limit to control driver in real-time. Also speedometer currently managed provide the driver warning information in real-time, but using only the speed of vehicle and RPM information regardless of actual dangerous drive behaviors, disappear the effectiveness. In this study performed a simulation for drivers in general using a simulator programed with dangerous driving types we had developed in the previous study and judging the types. It'd be more effective system to provide the drivers warning information using weight valued in this study. However in this study is limited to apply weight as a result of simulation of drivers in general in actual situation should be made up the deficit based on information of driving type of actual commercial vehicles.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.137-144
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• 2004

The real-time traffic information is considered to be the system to alleviate traffic congestion. An effective traffic information will help drivers make efficient travel decision, and network performance will be improved. To make efficient strategy of providing information, the analyst should quantify reduced congestion by the media traffic informations. Many other route diversion models considered only media-informations as information sources and ignored the impact of on-site informations such as visible delays and average speeds, which affect drivers' route diversion decision in practice. In those models, the effect of on-site informations could be treated to be the effect of media informations, and the effects of media informations would be over-estimated. The proposed model including the impact of on-site information can estimate the effect of media-informations. The results are expected to be applied to the analysis of traffic management policy such as ITS.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.49-57
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• 2010

This case study investigated red light violations at CBD, suburban and rural signalized intersections in chungbuk. The goal of this study is to understanding the collection between red light violations and various driver, vehicles and environmental factors. This study uses descriptive statistics analysis and logistics analysis with SPSS 12.0 software. The major results of this study are as follows. First, red light violations occurred at rural and CBD more than suburban area. Second, About 81.1% of the violators were traveling at or below the posted speed limit. Moreover, 77.3% of the violations occurred within 2 seconds after the on set of red light. Finally, the logistic regression model, which is statistically significant(chisquare=0.000, McFadde=0.265)was developed, and includes the local type(CBD/suburban/rural), violators' gender, season, vehicle type, time of day, vehicle speed as the independent variables. In this study did not find significant relationship between red light violators' age and their driving behavior approaching signalized intersections.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.111-120
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• 2007

More accurate vehicle trajectory data are now readily available through Differential Global Positioning Systems (DGPS). A variety of research opportunities emerge with utilization of such high resolution traffic data. A novel approach of this study is to explore drivers' responsive behavior to variable message signs (VMS) by using individual vehicle trajectories extracted from in-vehicle DGPS data. Responsive characteristics of drivers traveling on urban freeways, which can be represented by speeds and acceleration rates, under the provision of real-time traffic information through VMS are statistically investigated. In addition to conducting an ANOVA test, probability density functions of acceleration rates were estimated. The findings of this study can be used to understand the impact of drivers' workload when providing VMS messages on traffic flow patterns. Furthermore, results can be important fundamentals to assist in conducting more realistic traffic simulations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.167-175
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• 2020

The Two-fluid Model, proposed by Herman and Prigogine in 1979, is a macroscopic model for describing network operability in urban networks. Since the Two-fluid Model parameters change according to the traffic flow characteristics, it is necessary to identify the cause of flow change when analyzing the operability using the parameters. This study compared the crash risk according to rainfall using the Two-fluid Model parameters, and explained that the driving behavior affects the operability of the urban network. The results of the parameters estimation showed poor network operation under rainfall condition. The factors of drivers' crash risk perception model were calculated, and driving behavior was analyzed due to crash risk according to rainfall. In both the morning and evening, drivers tended to slow down their speeds to reduce the crash risk, because the risk on rainy days could be high when the speed was the same as on a sunny days. However, the crash risk was still higher on rainy days than sunny. In the future, it is necessary to analyze the relationship between the network operation and the crash risk in various networks and to improve both.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.43-52
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• 2023

Traffic accidents among children have been decreasing after the installation of yellow carpets. However, the explanatory power of the causal relationship between yellow carpet installation and traffic accidents is still insufficient. The yellow carpet effect was analyzed in greater depth using virtual reality (VR) simulation experiments in various situation that could not be evaluated in existing actual vehicle research studies due to difficulties or risks in implementation. A target site where an actual yellow carpet was installed was selected and, implemented into a virtual environment. Subjects were made to, were gaze measurement equipment and ride the simulator. The visual/driving behavior before and after yellow carpet installation was compared, and a t-test analysis was performed for statistical verification. All the results were found to be statistically significant.