• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.3
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• pp.52-59
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• 2008

Most accident reconstruction or analysis depend on the coefficient of friction to estimate the vehicle speeds. Skid mark and coefficient of friction are usually utilized to calculate the velocity and behavior of vehicles. For a critical case such as traffic accident reconstruction, however, the initial velocity of the car should be calculated precisely. In this paper, emergency brake tests on ABS and Non-ABS brake system are conducted on the dry pavement asphalt road on speed 40, 60, 80 and 100 km/h respectively. The SWIFT sensor was established in the front wheel and rear wheel at driver side to measure the forces, moments and speeds of revolution of the tires. These tests results can be available to brake tests and accident reconstruction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.54-62
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• 2010

The scientific analysis of car-pedestrian accidents is not an easy task because of the characteristic of the accidents itself. Since the analysis involved human being, there were few experimental data that could be used for the analysis. The coefficient of friction of human body was the one of crucial data for accident analysis, but no field experiment report was available for various roadway conditions. This study intends to measure the coefficient of friction of human body through field studies. Results showed that the coefficient of friction of human body for dry asphalt pavement conditions was 0.59~0.62, and for dry concrete pavement conditions was 0.59~0.61. In addition, the coefficients for wet asphalt pavement and for wet concrete pavement conditions were 0.56~0.59 and 0.51~0.54 respectively, indicating 5.0% and 8.3% reduction compared to the dry conditions. The deduced coefficients were validated using the simulation program. It has been confirmed that the experiment values were close to the simulation results.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.109-114
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• 2007

Skid mark and coefficient of friction are usually utilized to calculate the velocity and behavior of vehicles. For a critical case such as traffic accident reconstruction, however, the initial velocity of the car should be calculated precisely. In this study, the skid marks on dry asphalt pavement were measured, and the velocity at brake onset was precisely recovered. A passenger car with new tires and non-contact optical speedometer were set up for the tests. A new methodology to determine the more precise velocity for Non-ABS vehicle at braking onset were suggested.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.78-87
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• 2021

This study is to evaluate the applicability and performance of trapezoidal-shaped grooves on domestic airport runways. For this, the constructability, drainage performance, and friction resistance characteristics of trapezoidal-shaped grooves compared to square-shaped grooves were evaluated through test construction on pavement at Incheon Airport. As a result of the test construction, the trapezoidal-shaped grooves satisfies the required geometry standards and tolerance, and secured a macrotexture that was 25% improved compared to the square-shaped grooves. It was confirmed that trapezoid-shaped grooves secured drainage performance of more than 7-9%, and surface friction performance improved compared to existing grooves when the surface of the pavement was wet as the test speed increased in the dry state. In addition, after trapezoidal-shaped grooves was installed on the RWY 16R/34L of Incheon Airport, the friction coefficient was 0.84, which satisfies the design level of the new runway surface of 0.82 at the test speed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.82-89
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• 2024

Black ice is very difficult to recognize and reduces the friction of the road surface, causing automobile accidents. Since black ice is difficult to detect, there is a need for a system that identifies black ice in real time and warns the driver. Various studies have been conducted to prevent black ice on road surfaces, but there is a lack of research on systems that identify black ice in real time and warn drivers. In this paper, an real-time image-based analysis system was developed to identify the condition of asphalt road surface, which is widely used in Korea. For this purpose, a dataset was built for each asphalt road surface image, and then the road surface condition was identified as dry, wet, black ice, and snow using deep learning. In addition, temperature and humidity data measured on the actual road surface were used to finalize the road surface condition. When the road surface was determined to be black ice, the salt spray equipment installed on the road was automatically activated. The surface condition recognition system for the asphalt concrete pavement and black ice automatic prevention system developed in this study are expected to ensure safe driving and reduce the incidence of traffic accidents.