• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.105-115
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• 2011

In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• 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.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.378-383
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• 2012

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.150-156
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• 2017

A frozen road surface increases traffic accidents during the winter season. Hence, information on easily-frozen road sections and their specificities are required to prevent traffic accidents. Frozen road surfaces are determined by equipment measuring road surface temperatures. However, there are limitations in investigating the entire road network. Therefore, it is imperative to develop new methods that effectively determine road surface freezing risks. Meteorologically, road surfaces are frozen when the actual temperature cools down to the dew point temperature. Under this condition, there is likely to be frost if relative humidity reaches 100% and frozen road surfaces as the temperature gets lower. Meteorological characteristics give us an alternative to a direct measurement road surface temperature to estimate risks of road surface freezing. Based on the clues, the relationship between severity of traffic accidents and temperature changes is empirically investigated using Paju weather data. The results reveal that as the temperature gets lower and changes in current temperature are relatively small, the severity of traffic accidents become higher. In addition, the same is true when the difference between current temperature and the dew point temperature is relatively small, as it increases possibilities of road surface freezing. Future studies must investigate how current temperature and the dew point temperature affect road surface freezing and thereby establish a time-space scope to estimate possible road surface freezing sections using only weather and road material type data. This would provide invaluable information for predicting and preventing frozen road accidents based on weather patterns.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.35-44
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• 2017

PURPOSES: This study suggests a specific methodology for the prediction of road surface temperature using vehicular ambient temperature sensors. In addition, four kind of models is developed based on machine learning algorithms. METHODS : Thermal Mapping System is employed to collect road surface and vehicular ambient temperature data on the defined survey route in 2015 and 2016 year, respectively. For modelling, all types of collected temperature data should be classified into response and predictor before applying a machine learning tool such as MATLAB. In this study, collected road surface temperature are considered as response while vehicular ambient temperatures defied as predictor. Through data learning using machine learning tool, models were developed and finally compared predicted and actual temperature based on average absolute error. RESULTS : According to comparison results, model enables to estimate actual road surface temperature variation pattern along the roads very well. Model III is slightly better than the rest of models in terms of estimation performance. CONCLUSIONS : When correlation between response and predictor is high, when plenty of historical data exists, and when a lot of predictors are available, estimation performance of would be much better.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.553-568
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• 2015

This paper focuses on the geographical characteristics and the spatial distributions and patterns of the road names in the new address system for which all the 183 road names of Cheongju City has been used. All 183 road names in Cheongju City and their textural information are analyzed and classified into four main categories and six divisions as sub-category. Each type is mapped and its spatial patterns are discussed in order to identify the interaction between the road name and the geographical characteristics of each type. From the discussion stated in the paper, it can be inferred that the road name is not only a representative place name in an area, but also presents an important geographical feature reflecting the toponymy of the cultural and historical backgrounds of an area. Therefore, it is necessary to recognize that for road naming, various aspects such as geographical backgrounds and characteristics should be considered. These are directly related to the publicity and utilization of the road names to the public who is still unfamiliar with the new address system to be used. Finally, various geographical topics and approaches such as toponymy and spatial analysis are proposed for further geographical research, which will contribute to the extent of geographical research scopes.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.156-172
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• 2020

The purpose of this study was to predict road surface temperature using high-resolution solar radiation data. The road surface temperature prediction model (RSTPM) was applied to predict road surface temperature; this model was developed based on the heat-balance method. In addition, using SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry-model), the shadow patterns caused by the terrain effects were analyzed, and high-resolution solar radiation data with 10 m spatial resolution were calculated. To increase the accuracy of the shadow patterns and solar radiation, the day that was modeled had minimal effects from fog, clouds, and precipitation. As a result, shadow areas lasted for a long time at the entrance and exit of a tunnel, and in a high-altitude area. Furthermore, solar radiation clearly decreased in areas affected by shadows, which was reflected in the predicted road surface temperatures. It was confirmed that the road surface temperature should be high at topographically open points and relatively low at higher altitude points. The results of this study could be used to forecast the freezing of sections of road surfaces in winter, and to inform decision making by road managers and drivers.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.31-43
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• 2012

Domestic road type-and period-specific driving pattern measurement was required as Korea's participation in developing "Worldwide harmonized light-duty vehicle emission test procedure (WLTP/DHC)" studied by UN WP29. This study measured road driving data reflecting road and traffic conditions of Korea, and analyzed seven types of representative road type-and period-specific driving patterns with driving pattern standardization methodology proposed by WP29. PAMS (Portable Activity Monitoring Systems) equipment was used to collect enormous (35,410km) road driving data. There are significant difference among seven derived driving patterns.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.9-14
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• 2002

The durability prediction of emission control components, especially 02 sensor and catalytic converter, is getting more important as emission regulation is getting stricter and vehicle durability mileage requirement is also extended from 80,000 ㎞ to 160,000 km in Korean market. And the duration of vehicle mileage accumulation to get vehicle exhaust emission deterioration factor for certification is required to be shorter in order to reduce the vehicle development time. Since most of the vehicle emission development tests are done on chassis dynamometer and aging bench by using vehicle aging modes, real road condition and in-use driving patterns must be reflected into them to predict the vehicle emission level and to meet emission regulation especially at high mileage. In order to get the frequent driving pattern of vehicle and the aging characteristic of emission components, a vehicle was tested by changing drivers and driving roads around Seoul. Real road driving patterns were analyzed and compared with those of the certification modes which are well known in automotive industry.