• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.138-143
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• 2005

In order to reduce traffic accident, the interaction between drivers and roads should be studied in drivers' behaviour standpoints, and then this must be applied to the establishment of the road design standard. The K-ROADS(KICT-Road Analysis Driving Simulator) was developed to analyze and evaluate the road safety at the project HuRoSAS(Human & Road Safety Analysis System), since 2003. This has two distinct functions. One is the visual system which has 360 degree F.O.V. to reduce a dead angle on black spots as at-grade intersection. The other is the motion system which reproduce high frequency vibration made in irregular road surface and vehicle's motion. The K-ROADS has been used the study on the effect of alternatives of speed hump, and the study on the interior wall design of long tunnel to safety standpoints.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.235-249
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• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.117-132
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• 2021

Due to the terrain in Korea, there are many road sections passing through mountainous areas. During the winter, there is a higher risk of traffic accidents, due to black ice caused by the lack of sunlight. Despite domestic road freezing safety measures, accidents caused by road freezing results in severe traffic accidents. Under these considerations, this study analyzed whether traffic safety signs that change in response to the external temperature help drivers recognize frozen road segments. The study was conducted through analysis of the effect of the signs on a driver's perspective. For the signs under development, out of the signs designed by experts, the sign design which received the highest visibility and effectiveness evaluation ratings from the general public was selected. The sign was implemented through Virtual Reality (VR) and installed on the right side of the road to analyze the effect on gazing and driving behavior. As a result of analyzing the driver's driving behavior, a speed reduction of about 7km/h or more was found in the sign section. Therefore, It was found that the existence of the sign had a strong relationship with the rate of the drivers' speed reduction.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.107-120
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• 2011

Traffic signal is one of the major factors that affect the amount of vehicle emissions on urban highway. The amount of vehicle emissions in urban area is highly affected by the vehicle's cruising speeds heavily influenced by the traffic signal lighting conditions. It was attempted in this study to trace the changing patterns of the vehicle emissions by collecting the emission data from a set of simulation studies and by categorizing vehicle cruising conditions into four different groups: idling, acceleration, deceleration, and running at a constant speed. Authors propose a simple emission model prepared based on Kinematic theory. The validation test results showed that the amount of the emission estimated by the proposed model was relatively satisfactory compared to the one of the existing model employing the average speed data only as the determinant.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.37-45
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• 2011

The main objective of this study is two-fold: 1) to analyze the effect of PG technology application on road user's satisfaction and driving speed, and 2) to investigate the relationship between driver's subjective workload level and their reactions related to the PG technology application. Based on the result of field observation, the experimental scenario for driving simulation study was prepared. The experimental results showed that drivers were more satisfied to the road condition with PG technology applied, and even the pattern of speed reduction was more stable than control condition. The pattern of speed reduction along driver's subjective driving workload level were slightly different by physical road condition, and road user's satisfaction was revealed to be negatively correlated with their subjective driving workload level. This result indicates that depending on situation and driver characteristic, information for the drivers could be nothing more than nuisance that just distracts drivers. In order to facilitate the implementation of PG technology in Korea, further study on related human factors, especially for those who are weak in traffic situations, is recommended.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.31-43
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• 2019

Take-overs occur in autonomous vehicles at levels 3 and 4 based on SAE. For safe take-over, it is necessary to set the time required for diverse drivers to complete take-over in various road conditions. In this study, take-over time and stabilization characteristics were measured to secure safety of take-over in autonomous vehicle. To this end, a virtual driving simulator was used to set up situations similar to those on real expressways. Fifty drivers with various sexes and ages participated in the experiment where changes in traffic volume and geometry were applied to measure change in takeover time and stabilization characteristics according to various road conditions. Experimental results show that the average take-over time was 2.3 seconds and the standard deviation was 0.1 second. As a result of analysis of stabilization characteristics, there was no difference in take-over stabilization time due to the difference of traffic volume, and there was a significant difference by curvature changes.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.139-145
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• 2017

PURPOSES : This study analyzed the difference in a driver's workload between using a driving simulator and field driving in tunnel, highway. METHODS : Based on the literature review, it was found that a driver's workload could be quantified using biosignals. This study analyzed the biosignal data of 30 participants using data collected while they were using a driving simulator and during a field test involving tunnel driving. Relative energy parameter was used for biosignal analysis. RESULTS : The driver's workload was different between the driving simulator and field driving in tunnels, highway. Compared with the driving simulator test, the driver's workload exhibited high value in field driving. This result was significant at the 0.05 level. The same result was observed before the tunnel entrance section and 200 m after the entrance section. CONCLUSIONS : This study demonstrates the driving simulator effect that drivers feel safer and more comfortable using a driving simulator than during a field test. Future studies should be designed considering the result of this study, age, type of simulator, study site and so on.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.246-263
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• 2023

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.67-78
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• 2011

This paper analyzes the characteristics of drivers' workload observed from with 30 participant drivers with respect to two physio-physiological parameters. For investigating physio-physiological characteristics of road drivers, bio-signals from brain's occipital lobe between simulation experiment and real driving experiment are collected and analyzed. The major findings from the analysis are summarized as follows: First, the drivers' physio-physiological workload is a good parameter for explaining the workload characteristics of road drivers. Secondly, the two physio-physiological workload parameters selected, i.e., beta value and relative energy parameter, are revealed to be statistically significant. Thirdly, it is also revealed to be statistically significant to select 90 percentile measurements in simulator experiment to explain the road drivers' characteristics. Finally, the maximum workload of road design driver is 31.72 in beta parameter, whereas the minimum workload is 1.296 in relative energy parameter.