• International Journal of Highway Engineering
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• v.7 no.2 s.24
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• pp.87-95
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• 2005

To prevent the lowering of structural capability due to freezing and thawing in cold winter, numerous researches on frost heaving have been performed. As the result, the freezing index contour map of the Korea peninsula has been made for the design of the anti-freezing layer of pavements. However, the validity of the anti-freezing layer needs to be evaluated because systematic investigations on the variation of freezing depth with the thickness and material types of pavement layers and the configuration of the ground have been rarely performed. The freezing index of the Korea Highway Corporation test road site was calculated and the freezing depths of the concrete and asphalt pavements of the test road were investigated using the ambient and pavement temperature and water content. In addition, the investigated freezing depths were compared to the values estimated by existing freezing depth models. This is the preliminary study on the freezing-related data measured at the test road. The results with higher reliability will be produced by the long-term accumulation of the data and the analysis on it.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.1-8
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• 2016

PURPOSES : This study evaluates the reliability of the patterns of changes in the road surface temperature during winter using a statistical technique. In addition, a flexible road segmentation method is developed based on the collected road surface temperature data. METHODS : To collect and analyze the data, a thermal mapping system that could be attached to a survey vehicle along with various other sensors was employed. We first selected the test route based on the date and the weather and topographical conditions, since these factors affect the patterns of changes in the road surface temperature. Each route was surveyed a total of 10 times on a round-trip basis at the same times (5 AM to 6 AM). A correlation analysis was performed to identify whether the weather conditions reported for the survey dates were consistent with the actual conditions. In addition, we developed a method for dividing the road into sections based on the consecutive changes in the road surface temperature for use in future applications. Specifically, in this method, the road surface temperature data collected using the thermal mapping system was compared continuously with the average values for the various road sections, and the road was divided into sections based on the temperature. RESULTS : The results showed that the comparison of the reported and actual weather conditions and the standard deviation in the observed road surface temperatures could produce a good indicator of the reliability of the patterns of the changes in the road surface temperature. CONCLUSIONS : This research shows how road surface temperature data can be evaluated using a statistical technique. It also confirms that roads should be segmented based on the changes in the temperature and not using a uniform segmentation method.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.5
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• pp.90-99
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• 1996

To keep up with the regulation of OBD II(on board diagnostics II), many detection methods for engine misfire have been developed. Among them, the method of using the crankshaft speed fluctuation is the most noticeable in the point of view of lower cost and easier installation than any others. On the basis of the results obtained from the previous engine-dynamometer test, the integrating torque index (ITI) has been introduced. In this research, the instrumental and the interfacing systems to engine control unit(ECU) are developed for the vehicle test. Therefore, the vehicle and chassis-dynamometer test can be carried out in addition to the rough road test. From this test, the previousproposed method proved that it can be applied to the real vehicle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.202-217
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• 2021

Following the fatal accident of pedestrians caused by Autonomous Vehicle by Uber, the world's largest ride-hailing company, two people were killed in a self-driving car accident by Tesla in April. There is a need to ensure the safety of road users. Accordingly, in order to secure the safety of Autonomous Vehicle driving, it is necessary to evaluate Autonomous Vehicle driving technologies in various situations based on the road and traffic environment in which the Autonomous vehicle will actually drive. Therefore, this study used UC-win/Road ver.14.0 based on general driver's license test questions to present a virtual reality-based Autonomous Vehicles driving ability evaluation tool among various driving ability test method. Based on this, it was intended to test driving ability for unexpected situations in complex and diverse driving environments, and to confirm its practical applicability as an optimal tool for Autonomous vehicle ability test and evaluation.

• Journal of Digital Policy
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• v.2 no.4
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• pp.1-10
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• 2023

This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.23-31
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• 2016

PURPOSES : This study aimed to offer a greenhouse gases table to assist a road designer in calculating the greenhouse gases for a road environment when making a decision about an alternative road. METHODS : This study developed an operation mode table of greenhouse gases using the MOVES program. Similar factors for Korean vehicles and fuels are reflected in the MOVES program, which was made in the USA. Finally, a paired t-test was conducted to calculate the site data and MOVES data. Through these studies, a methodology was suggested for calculating carbon emissions based on various types of roads alignments. RESULTS : The site results for a passenger truck on the road were statistically significant when the vehicle speed was above 65 km/h. However, a future study will consider factors for various road alignments and vehicles. CONCLUSIONS : This study will contribute to the theoretical basis for reducing carbon emissions from roads by helping road designers make decisions about road alternatives in terms of the road environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.228-241
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• 2021

This study verified the performance change of a LiDAR when it detects road signs, which are potential cooperation targets for an autonomous vehicle. In particular, road signs of different colors and materials were produced and tested in controlled rainfall on the real road environment. The NPC and intensity were selected as the performance indicators, and a T-Test was used for comparison. The study results show that the performance of LiDAR for the detection of road signs was reduced with the increase of rainfall. The degradation of performance in retroreflective sheets was lesser than painted road signs, but at the amount of 40 mm/h or more, the detection performance of retroreflective sheets deteriorates to an extent that data cannot be collected. The performance level of black paint was lower than that of other colors on a clear day. In addition, the white sheet was most sensitively degraded with the increase in precipitation. These performance verification results are expected to be utilized in the manufacturing of road facilities that improve the visibility of sensors in the future.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.45-55
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• 2012

PURPOSES : Skid resistance and noise of roads highly depend on the characteristics of pavement texture. Therefore, estimation of texture characteristics may give useful information for the skid resistance and noise of road. Generally, Sand Patch Test is performed in order to estimate MTD(Mean Texture Depth). However, it is time-consuming and needs traffic control. This study aimed to investigate the effectiveness of measurement texture depth using the Portable Laser Profiler that give the MPD(Mean Profile Depth). METHODS : MTD and MPD were collected on the number of expressway sections including Central Inland Test Road sections in Korea. Statistical analysis are performed to establish the relationship between MTD data based on Sand Patch Test and MPD data obtained by the Portable Laser Profiler. RESULTS : Linear relationship MPD and MTD is observed for both of asphalt pavement and concrete pavement such as R-square of 0.51 to 0.58. CONCLUSIONS : Even though, the test method and definition of MPD and MTD are different. EMTD(Estimated Mean Texture Depth) can be obtained by using the correlationship between MPD with MTD.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.69-76
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• 2015

Although traffic information has been actively analyzed using big data, it has not been used as much with the consideration of driver characteristics. Among the various types of information, road signs can directly affect the driver. Road signs must provide the optimal information that enables drivers to reach their destinations with ease as well as information suitable for navigation systems. However, present road sign rules provide standardized information, regardless of the road type or size. This study suggests a method for providing road information that will help drivers determine their behavior. First, the minimum character size that can be used on a road sign for each design speed was obtained with respect to the visibility and decipherability of a road sign. Instead of conventional diagram-based direction guidance, a scenario using split-based direction guidance was created. To verify the effectiveness of the provided information, a three-dimensional simulated road environment was constructed, and a driving simulator was used for the test. At a simple plane intersection, the driver was not greatly influenced by directional guidance, but at a complex, three-dimensional intersection, the driver preferred summary-based directional guidance, which is instinctive guidance, over diagram-based guidance. On the basis of the test results, a secondary verification test that applied split-based guidance at a three-dimensional intersection confirmed that the driver had no problems in making decisions.