• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.1
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• pp.15-31
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• 1996

The purpose of this study was to figure out visual character and preference of roadscape for the main entrance road in Chongju. We took 9.6km which was from the Chongju interchange of Kyungbu expressway to Sangdang park and was thought to have a peculiar characteristics. This main entrance road was seperated into 4 parts according to arranging patterns of roadside trees and buildings. To investigate the visual characters, the sementic differential scale experiment was used. The visual characters, the sementic differential scale experiment was used. The visual preference was examined by analyzing visual volume of 4 factors. The results of the study based on these analyses were as below : 1. Factors that compose the visual characters of roadscape were classified by the emotional factor, the individual factor and the physical factor. These 3 factors showed a64.14% total variance. Among 3 factors the emotional factor which represented psychological reaction was appreciated to be the highest and the physical factor was assessed to be the lowest. 2. 24 items in total 14 adjectives showed the following ranking of mean values in sementic differential experiment : Road I -->RoadIII-->RoadII-->RoadIV. The mean values between Road I and RoadIV showed a significant difference, which can be explained to be a contrast between the natural factor and the artificial factor. 3. The mean value of the visual preference was the highest at Road I and the lowest at Road IV. While Road II and Road III showed 3.51 and 4.71, respectively. 4. The effect of 4 factors on visual preference was analyzed by regression as follows : Visual preference =1.2983+0.0627 + 0.0230+0.0203, R-Square=0.5

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.759-764
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• 1998

We propose a novel algorithm capable of recognizing the road lane by image processing. Considering the fact that the direction and location of road lane are maintained similarly in successive images we formulate a function to represent the property. However, as noises play the role of making a lot of similar patterns appear and disappear in the road image, keeping of robustness in the lane detection has been known a difficult work. To overcome this problem, we introduce the following three ideas: 1) design of a function based on an edge direction and magnitude, 2) construction of a recursive filter to estimate the function recursively for successive images, 3) principal axis-based line fitting. These concepts enhance the adaptability to cope with the random environment of traffic scene and eventually lead to the reliable detection of a road lane.

• Korean Journal of Ecology and Environment
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• v.38 no.spc
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• pp.58-61
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• 2005

Environmental polluting materials from road surface drainage are a significant nonpoint source influenced to the eutrophication of lake and ecosystems with a transport development in recent years. To elucidate the discharge characteristics, the changing patterns in concentrations of polluting materials such as suspended solid (SS), chemical oxygen demand (COD), nitrogenous and phosphorus nutrients in drainage waters, were investigated during rainfall. Load variation of COD concentration in drainage water samples was closely related to that of SS concentration. This indicates that SS contained a greater part of organic matter. A quite difference between the past pavement and the new well-drainage pavement system was observed in the concentrations of SS and COD in drainage waters. Appreciable concentrations of nitrite and nitrate were determined in drainage waters. The present results indicate that the drainage water from road surfaces is a significant nonpoint source, and that the well-drainage pavement system introduced to skid prevention has an effect on the decreases of pollutants.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.61-67
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• 2016

OBJECTIVES : The objective of this study is to detect road cavities using multi-channel 3D ground penetrating radar (GPR) tests owned by the Seoul Metropolitan Government. METHODS : Ground-penetrating radar tests were conducted on 204 road-cavity test sections, and the GPR signal patterns were analyzed to classify signal shape, amplitude, and phase change. RESULTS : The shapes of the GPR signals of road-cavity sections were circular or ellipsoidal in the plane image of the 3D GPR results. However, in the longitudinal or transverse direction, the signals showed mostly unsymmetrical (or symmetrical in some cases) parabolic shapes. The amplitude of the GPR signals reflected from road cavities was stronger than that from other media. No particular pattern of the amplitude was found because of nonuniform medium and utilities nearby. In many cases where road cavities extended to the bottom of the asphalt concrete layer, the signal phase was reversed. However, no reversed signal was found in subbase, subgrade, or deeper locations. CONCLUSIONS : For detecting road cavities, the results of the GPR signal-pattern analysis can be applied. In general, GPR signals on road cavity-sections had unsymmetrical hyperbolic shape, relatively stronger amplitude, and reversed phase. Owing to the uncertainties of underground materials, utilities, and road cavities, GPR signal interpretation was difficult. To perform quantitative analysis for road cavity detection, additional GPR tests and signal pattern analysis need to be conducted.

• Journal of ILASS-Korea
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• v.21 no.4
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• pp.214-222
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• 2016

Changes in road infrastructure affect driving patterns and pollutant emission characteristics. we analyzed the changes in driving patterns and pollutant emission characteristics of the driving route via measured driving patterns at year 2009 and 2016. Since 2009, there has been an increase in population and traffic demand, including residential areas and industrial facilities. Traffic conditions were improved such as the opening of the highway Inter-Change to Seoul and the construction of underground driveway. As a result, the average vehicle speed increased. More detail comparisons have made on the changes of the underground driveway section and the crossroad section, which are expected to have significant changes in the transportation infrastructure. The vehicle speed distribution of the underground driveway changed from low speed to high speed, and the increase of the time spent at the high speed and high load caused the increase of NOx emissions. The vehicle speed also increased at the crossroad section, and the consequence NOx and $CO_2$ emissions decreased. It is mainly because the decreased time spent at idle, which results from the proper traffic demand management at this area.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.137-148
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• 2005

The position information of individual vehicles on a road at every time instant can be used to analyze the microscopic behaviors of driving of each vehicle. The limited information obtained from previous imaging technology such as traffic volume and interval velocity cannot be used to explore such microscopic traffic conditions. Also, information gathering for the microscopic behaviors by manual analysis of captured video takes large amount of time and man-power. In the paper we develop the rule-based vehicle tracking technology from which the position information of individual vehicles on a road at every time instant can be automatically obtained. Also, we extract the position data of driving vehicles on a road, length of 130m for every 0.05 second, and calculate the velocity of each traced vehicles to compare with the real velocity for the verification of accuracy. In the future, this type of tracking techniques based on video analysis can be widely used to provide the practically important information of road traffic conditions and to analyze the academically important microscopic behaviors of driving patterns.

• Journal of ILASS-Korea
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• v.22 no.4
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• pp.218-224
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• 2017

In order to improve the quality of air in urban areas, the emission regulations are being strengthened by the government. The on-road test of light-duty vehicles was started with PEMS because certification test mode does not sufficiently reflect on-road conditions. Therefore, The PEMS-based test was implemented from Sep. 2017 in Europe and Korea. However, this is lack of data on various on-road patterns in Korea. The purpose of the present study has analyzed the effect of speed per acceleration and acceleration on NOx emission on-road driving. The test route consisted of urban, rural, and motorway in Seoul. This study has been conducted by Euro-6 vehicles using on SCR system with PEMS. The on-road emission characteristics were evaluated by moving averaging windows (MAW) method. In results, RDE-NOx by severe driving pattern has been 1.4 times higher than soft driving pattern NIER Route 1.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.487-489
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• 1998

To evaluate vehicle performances and driving behavior of a vehicle, it is necessary to acquisit and analyze vehicle data during the vehicle driving, which affect fuel economy and emissions. An in-vehicle data acquisition system, which is called Mode Survey System(MOSS), is designed and developed to analyze the traffic and driving patterns of the vehicle. MOSS is a stand-alone system based on the 68HC11 MCU. MOSS logs various data relating to powertrain and vehicle driving such as vehicle speed, engine RPM, gear position, brake, clutch, fuel consumption, and others. The driving patterns are dependent on the driver's habit and the road and traffic conditions, these driving patterns would be able to make a official driving mode to be used in emission, fuel efficiency, shift survey, catalyst durability, and other tests using the analyzed driving patterns.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.582-590
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• 2015

Road type classification and K-factors are important role when design of number of lane. In this study not only classifies road type and estimating of K-factor but also economic evaluation tries for feasibility verification. Road type analysis results, time of day traffic volume variation, weekend-factor and vacation-factor are large in recreation roads. Weekday traffic volume and weekend traffic volume are similar patterns in provincial roads. AADT is high and time of day traffic volume variation is small in urban roads. In this study compares with economic analysis that designing of number of lane between KHCM's K-factor and this study K-factor. Economic analysis results, designed roads by this study's K-factor reduce cost about 4,708 hundred million won. So this study's K-factor is economical on provincial 4 lane roads.