• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.3
• /
• pp.59-72
• /
• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.5A
• /
• pp.673-683
• /
• 2008

This study improved the existing method of using the longitudinal strain and concept of influence line to develop Bridge Weigh-in-Motion system without axle detector using the dynamic strain of the bridge girders and concrete slab. This paper first describes the considered algorithms of extracting passing vehicle information from the dynamic strain signal measured at the bridge slab, girders, and cross beams. Two different analysis methods of 1) influence line method, and 2) neural network method are considered, and parameter study of measurement locations is also performed. Then the procedures and the results of field tests are described. The field tests are performed to acquire training sets and test sets for neural networks, and also to verify and compare performances of the considered algorithms. Finally, comparison between the results of different algorithms and discussions are followed. For a PSC I-girder bridge, vehicle weight can be calculated within a reasonable error range using the dynamic strain gauge installed on the girders. The passing lane and passing speed of the vehicle can be accurately estimated using the strain signal from the concrete slab. The passing speed and peak duration were added to the input variables to reflect the influence of the dynamic interaction between the bridge and vehicles, and impact of the distance between axles, respectively; thus improving the accuracy of the weight calculation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.1
• /
• pp.9-21
• /
• 2009

This study presents a useful heuristic algorithm to classify vehicle classes using vehicle length information, which is extracted from inductive loop vehicle signatures. A high-speed scanning equipment was used to extract more detailed change of inductance magnitude for individual vehicles. Vehicle detection time and individual vehicle speeds were used to derive vehicle length information that is an input of the proposed algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm performance more systematically. It is expected that the proposed method would be useful for obtaining vehicle classification information from wide-spread existing loop infrastructure.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.6
• /
• pp.33-42
• /
• 2010

Travel speed is an important parameter in measurement of road traffic. UTIS(Urban Traffic Information System) was developed as a type of section detector. However, UTIS incur errors caused by irregular vehicle trajectories, wireless communication range and so on. This paper suggests a new model that use an error-filtering algorithm to improve the accuracy of travel speed measurements. In the field test, the variance of the percent errors measured by the new model was reduced. Therefore, it can be concluded that the proposed model significantly improves travel speed measuring accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3D
• /
• pp.461-467
• /
• 2006

To detect individual vehicular speed, double loop detection technique has been widely used. This paper investigates four methodologies to measure individual speed using only a single loop sensor in a traveling lane. Two methods developed earlier include estimating the speed by means of (Case 1) the slop of inductance wave form generated by the sensor and (Case 2) the average vehicle lengths. Two other methods are newly developed through this study, which are estimations by measuring (Case 3) the mean of wheelbases using the sensor installed traversal to the traveling lane and (Case 4) the mean of wheel tracks by the sensor installed diagonally to the traveling lane. These four methodologies were field-tested and their accuracy of speed output was compared statistically. This study used Equality Coefficient and Mean Absolute Percentage Error for the assessment. It was found that the method (Case 1) was best accurate, followed by method (Case 4), (Case 2), and (Case 3).

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.115-131
• /
• 2022

Carbon dioxide (CO₂) emissions from the transportation sector in South Korea accounts for 16.5% of all CO₂ emissions, and road transportation accounts for 96.5% of this sector's emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO₂ emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO₂ emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model-which was developed to obtain second-by-second vehicle activity data and analyze daily CO₂ emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO₂ were emitted per day at each intersection. This study reveals a new possibility of analyzing CO₂ emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO₂ emission analyses.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2003.11a
• /
• pp.208-212
• /
• 2003

An airborne radar is an essential aviation electronic system of the helicopter to perform various missions in all-weather environments. This paper presents the conceptual design results of the multi-mode pulsed Doppler radar system testbed model for helicopter. Due to the inherent flight nature of the hovering vehicle which is flying in low-altitude and low speed, as well as rapid maneuvering, the moving clutters from the platform should be suppressed by using a special MTD (Moving Target Detector) processing. For the multi-mode radar system model design, the flight parameters of the moving helicopter platform were assumed: altitude of 3 Km, average cruising velocity of 150knots. The multi-mode operation capability was applied such as short-range, medium-range, and long-range depending on the mission of the vehicle. The nominal detection ranges is 30 Km for the testbed experimental model, but can be expanded up to 75 Km for the long range weather mode. The detection probability of each mode is also compared in terms of the signal-to noise ratio of each mode, and the designed radar system specifications ate provided as a design results.

• Proceedings of the KIPE Conference
• /
• 2002.07a
• /
• pp.110-114
• /
• 2002

Generally, brushless DC motor(BLDCM) driving system uses hall sensors or encoders as the mechanical position or speed sensors. It is necessary to achieve the informations of rotor position for driving trapezoidal type brushless DC motor without any position sensor. This paper proposes a sensorless driving system with rotor absolute position detector circuit which acquires both commutate phase and commutate time by analyzing motor phase voltages. Proposed system is applied to a 10k[W] rating motor which actually used in electrical vehicles of HONDA co.,ltd. The experimental results will show the validity of the proposed system and the practical use of proposed sensorless drive algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.5
• /
• pp.473-479
• /
• 2009

This paper proposes an efficient method to locate the automated guided vehicle (AGV) into a specific parking position using artificial visual landmark and vision-based algorithm. The landmark has comer features and a HSI color arrangement for robustness against illuminant variation. The landmark is attached to left of a parking spot under a crane. For parking, an AGV detects the landmark with CCD camera fixed to the AGV using Harris comer detector and matching descriptors of the comer features. After detecting the landmark, the AGV tracks the landmark using pyramidal Lucas-Kanade feature tracker and a refinement process. Then, the AGV decreases its speed and aligns its longitudinal position with the center of the landmark. The experiments showed the AGV parked accurately at the parking spot with small standard deviation of error under bright illumination and dark illumination.

• Journal of Korea Multimedia Society
• /
• v.11 no.12
• /
• pp.1649-1657
• /
• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.