• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.150-156
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• 2011

Smart Highway is a next generation highway that significantly improves a traffic safety, reduces incidence of traffic accidents, and supports intelligent and convenient driving environments so that drivers can drive at high speeds in safety. In order to implement smart highway, it is required to gather a large amount of data including conditions of a road and the status of vehicles, and other useful data. To provide situation information of highway, it has been gathered traffic information using optical sensors(CCTV, etc.). However, this technique has problems such as the problem of information gathering, lack of accuracy depending on weather conditions and limitation of maintenance. It needs radar system which has not effect on environmental change and algorithm processing technique in order to provide information for a safety driving to driver and car. In this paper, it is used radar with 9.4GHz to test performance of a road surface and developed radar system for detecting test. And we compared and analyzed a performance of data acquired from each radar through computer simulation.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.51-59
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• 2016

OBJECTIVES : The objective of this study is to estimate the appropriate storage required for deicing materials in Gangwon-do for successful snow removal operations during the 2018 Pyeongchang Winter Olympic Games. The final estimates of the deicing chemicals can be used by public agencies to aid decision making. METHODS : First, the database that exists in the road snow-removal management system (RSMS) of the Ministry of Land, Infrastructure, and Transport, South Korea was used to determine historical characteristics of snow removal experiences in Gangwon-do. The database includes historical information, including regional and road weather data and number of snow-removal works. Second, both the maximum and the actual amount of storages used for deicing materials in the past three years were analyzed. Lastly, the final estimates of the deicing materials were evaluated using an additional equation. It considers frequency of salt spray application, total administrative road length estimated by road agencies, and number of days required for snow removal works in Gangwon-do. Consequently, the results show that significant differences were not observed between the final estimates and the maximum amount used during the past three years. RESULTS : The final estimates of the deicing materials are almost similar to the maximum amount used during the past three years in Gangwon-do. CONCLUSIONS : The study shows that the estimates of deicing chemicals can be useful when decision making is required for the snow-removal policy.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1177-1182
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• 2007

This study aims at identifying the effect of preferred visual and auditory stimuli on the road traffic noise perception through the series of psychoacoustic experiments. The first experiment was designed to find the addition effect of a sound reproducing system in a square where lay adjacent to roads with road traffic noise, provide appropriate music corresponding to the varying conditions of weather in the given space. In result, it was found that the rating around the square improved toward more positive adjectives. The second experiment was designed to assess the visual effect of twelve roadsides with different landscapes on the road traffic noise perception. As a result, approx. 3 to 5 dB(A) of psychological reduction was seen in places where natural landscape was preferred, compared to the others, although the noise levels were similar. The third experiment was designed to evaluate the effect of visual screen from adjacent roads on road traffic noise perception by means of ME method in a laboratory. In result, the effect of psychological reduction was observed at 65dB(A) or lower. Especially, complete screening from adjacent roads led to 5 to 10% of loudness reduction effect, compared to non-screening cases. Finally, the fourth experiment was designed to evaluate the effect of visual and auditory information with ME method and 7-point SD rating scale in a laboratory. In result, up to 10% of loudness reduction and about 2dB(A) of noise perceptional reduction were seen at 65dB(A) or lower.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.88-93
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• 2012

Lane detection methods using camera, which are part of the driver assistance system, have been developed due to the growth of the vehicle technologies. However, lane detection methods are often failed by varying road conditions such as rainy weather and degraded lanes. This paper proposes a method for lane detection which is robust in varying road condition. Lane candidates are extracted by intensity comparison and lane detection filter. Hough transform is applied to compute the lane pair using lane candidates which is straight line in image. Then, a curved lane is calculated by using B-Snake algorithm. Also, weighting value is computed using previous lane detection result to detect the lanes even in varying road conditions such as degraded/missed lanes. Experimental results proved that the proposed method can detect the lane even in challenging road conditions because of weighting process.

• Atmosphere
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• v.31 no.2
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• pp.157-170
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• 2021

To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.154-164
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• 2018

Purpose: Recent climate change makes weather-related disasters such as summer storms, heavy rains, winter snowfall disasters, and extreme cold temperature increase in trend. Heavy snowfall disasters requires speedy response due to various effects to traffic flows, buildings, and infrastructure. Heavy snowfall disaster response of South Korea is insufficient, even though heavy snowfall disasters affect urban safety. There have been lack of policy studies for heavy snowfall disasters. Method: This research analyzes case studies and explores implications using Information system technologies to snow removal vehicles and equipments for speedy snow removal during the heavy snowfall disasters. Results: Information system technology attachment to snow removal equipments can identify locations of snow removal vehicles and equipments for emergency period to support snow removal of adjacent jurisdictions. Conclusion: Case studies of this research can be further used for efficient application of snow removal tools of local governments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.269-279
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• 2020

Traffic estimation mainly involves surveying equipment such as automatic vehicle classification, vehicle detection system, toll collection system, and personnel surveys through CCTV (Closed Circuit TeleVision), but this requires a lot of manpower and cost. In this study, we proposed a method of estimating traffic volume using deep learning and stereo CCTV to overcome the limitation of not detecting the entire vehicle in case of single CCTV. COCO (Common Objects in Context) dataset was used to train deep learning models to detect vehicles, and each vehicle was detected in left and right CCTV images in real time. Then, the vehicle that could not be detected from each image was additionally detected by using affine transformation to improve the accuracy of traffic volume. Experiments were conducted separately for the normal road environment and the case of weather conditions with fog. In the normal road environment, vehicle detection improved by 6.75% and 5.92% in left and right images, respectively, than in a single CCTV image. In addition, in the foggy road environment, vehicle detection was improved by 10.79% and 12.88% in the left and right images, respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.106-112
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• 2012

Smart Highway is the intelligent highway that improves a traffic safety, reduces incidence of traffic accidents, and supports intelligent and convenient driving environment so that drivers can drive at high speeds in safety[1]. In order to implement the highway, it is required to gather a dangerous data such as obstacle, wild animal, disabled car, etc. To provide the situation information of the highway, it has been gathered traffic information using various sensors. However, this technique has problems such as the problems of various information gathering, lack of accuracy depending on weather conditions and limitation of maintenance. Therefore, in order to provide safe driving information to driver by gathering dangerous condition, radar system is needed. In this paper, we used a developing 34.5GHz RWR(Road Watch Radar) radar for gathering dangerous information and we verified performance of obstacle detecting and resolution through field test.

• Journal of environmental and Sanitary engineering
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• v.18 no.2
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• pp.42-51
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• 2003

Public awareness of air pollution problem has increased the need for real time air pollution information system about changes in air pollution level. The purpose of this study is to construct e-AIR, a user-friendly air pollution information system for urban air quality using GIS(geographic information system) technology for windows. GIS was ideally suited featuring a geographical characteristics(e.g., road, traffics, buildings) and very effectively used in mapping and symbolization for the distribution of the spatial/periodic pollution status(e.g., pie or column chart, graduated symbols) which can be effectively applied to a information system on the web-site. And a user interface, GUI(graphic user interface) was designed very diversely and simply enabled the users connect with e-AIR and obtain a useful information of air quality. A interpretive technique, air pollution health index(e.g., PSI, AEI) was used also which transforms complex data on measured atmospheric pollutant concentrations into a single number or set of numbers in order to make the data more understandable. Eventually the final-step of this study was to construct e-AIR based on Web GIS could be assessed anywhere if internet is available and offer a very useful information services of the air pollution to the public like a weather news.