• International Journal of Highway Engineering
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• v.12 no.3
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• pp.1-8
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• 2010

This study is performed to evaluate the physical and mechanical characteristics of an acryl polymer concrete that is developed as an overlay material for cement concrete slabs and pavements. Various laboratory tests including viscosity, flow, compressive strength, flexural strength, tensile strength, linear shrinkage, thermal expansion and thermal compatibility tests are performed. It is observed from the laboratory tests that the acryl polymer concrete developed in this study satisfies all the requirements suggested by ACI guideline. In addition to the laboratory tests, an accelerated performance testing (APT) is conducted to validate the performance of the acryl polymer concrete. During the APT, no significant distresses are observed until 15,903,939 cycles of equivalent single axle loading is applied. Finally, a 10mm thick overlay with the acryl polymer concrete is applied on top of an old deteriorated concrete pavement to evaluate field performance. Right after the field construction, skid resistance, noise and roughness are measured. The skid resistance and noise level have been significantly improved while the roughness is increased. Periodic investigation for the field study section will be conducted to evaluate the long-term performance.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.147-154
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• 2010

In post-tensioned concrete pavement(PTCP), one of the most important design variables is the initial joint width, in addition to the tensioning spacing. The joint width between PTCP slabs directly affects noise and ride quality. If the joint width is too wide, noise increases and ride quality decreases. If the initial joint width is too narrow, on the other hand, under high temperature, PTCP slabs can blow up, or failures near the joint can occur due to excessive compressive stresses. This study was conducted to determine the optimal initial joint width of PTCP and to investigate the joint width behavior under temperature changes. The experiments were performed using one-year-old PTCP slabs. The concrete temperatures were measured using the temperature measurement sensors installed at various depths. The joint widths were measured using vernier-calipers at different times of a day and the relationship between the joint width and temperature was analyzed. From this study, the design methodology to determine the optimal initial joint width of PTCP could be proposed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.87-92
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• 2010

As the Concept "how environmental friendly" becomes more and more important in road construction. However, so far there is no estimation method. Environmental friendly concept can be incorporated at the plan level in order to influence decision making, and support policies that affect environment. The overall goal of this study was to develop environmental friendly concept measures for the national highway and to develop a methodology to implement a more environmental friendly concept. The research identified 8 performance measures through a project analysis that could address environmental impact assessment system's ten strategic goals - Topography, Wildlife, hydrology, landuse, air quality, water quality, soil, waste, noise, landscape. The qualitatively and quantitatively evaluation approach was selected as the decision support framework and performance measure were investigated using the AHP(Analytic Hierarchy Process) and pilot corridor for a 10 section and calculate the index values. The methodology was applied to a pilot corridor comprised of a 120km section of national highway in korea. The methodology made it possible to identify the specific performance measures that need improvement to enhance the overall environmental friendly concept. It is fairly intuitive, based on readily available data, and is easy to apply. It provides a powerful tool for government to assess the relative environmental friendly conceptof their transportation corridors now and in the future. It allows for comparisons within a corridor and with other corridors and identifies the improvements needed to enhance the environmental friendly concept.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.188-199
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• 2013

This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions- horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.1
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• pp.21-28
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• 2004

We have demonstrated a low speed weigh-in motion system using FBG sensors and performed field test at a trial road. Technique, called identical chirped grating interrogation, have used for a demodulation relying on the mismatching of two identical broadband chirped gratings. We compensated the fluctuation of LED power and the temperature of sensor and used a lock-in amplifier to reduce effect of noise. We could design a bending plate that the measurement results are independent of position of weight. The FBG sensors weigh-in motion system showed linearity and reproducibility.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1166-1174
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• 2017

In general, the detection of the vehicle license plate is a previous step of license plate recognition and has been actively studied for several decades. In this paper, we propose an algorithm to detect a license plate area of a moving vehicle from a video captured by a fixed camera installed on the road using the Convolution Neural Network (CNN) technology. First, license plate images and non-license plate images are applied to a previously learned CNN model (AlexNet) to extract and classify features. Then, after detecting the moving vehicle in the video, CNN detects the license plate area by comparing the features of the license plate region with the features of the license plate area. Experimental result shows relatively good performance in various environments such as incomplete lighting, noise due to rain, and low resolution. In addition, to protect personal information this proposed system can also be used independently to detect the license plate area and hide that area to secure the public's personal information.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.659-665
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• 2000

In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.