• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• Journal of Korean Society of Transportation
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• v.13 no.3
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• pp.67-86
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• 1995

It requires the detector system which can collect highly reliable traffic data in order to perform the real-time traffic signal control. This study is to decide the optimal shape of inductive loop for the real-time traffic signal control .This loop is located at the stopline in the signalized intersection for DS(Degree of Saturation) control. In order to find out the optimal shape of loop, 6types of experiments were performed . The results of the basic experiments of loops are as follows ; -the optimal number of turns for loop is 3 turns. -the impedance values of the loop detectors are similar to that of NEMA standards -the 1.8${\times}$4.5M loop is excellent for sensitivity in actual detection range of car length comparing to other shape of inductive loops. At the experimental of establishments of the optimal loop shape, it found that 1.8 4.5M loop has the highest values of $\DeltaL$ comparing to other types of loops, It means that the range of Lead-in cable length of this loop. And this loop is highly reliable in occpupancy time. Conclusivley, the 1.8${\times}$4.5M inductive loop is the optimal solution as a stop line loop detector for real -time traffic signal control.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.89-118
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• 1996

The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2956-2958
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• 2000

This paper describes the design of a real time traffic data acquisition system using loop detector and piezzo sensor. Loop detector is the cheapest method to measure the speed and piezzo is used to detect the vehicle axle information. A ISA slot based I/O board is designed for data acquisition and PC process the raw traffic data and transfer the data to the host system. Simulation kit is designed with toy car kits. simulated loop detector and piezzo sensor. The data acquisition system collects up to 10 lane highway traffic data such as vehicle count. speed. length axle count. distance between the axles. The data is processed to generate traffic count, vehicle classification, which are to be used for ITS. The system architecture and simulation data is included and the system will be tested for field operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.22-35
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• 2013

With the increase in image detectors, concerns about the reliability of traffic information are increasing. In this paper, we propose a method to generate reliable traffic volume using analysis of the point detector data as a representative value. Therefore, targeting expressway, we analyzed the difference in traffic volume collected by loop and image detector, and verified statistically using t-test, and finally analyzed the error rate compare to the real traffic volume. Analysis revealed that there was a statistically difference the traffic date collected by the loop detector and the image detector, in the same period, the same time, respectively. In addition, the difference between the actual traffic volume and traffic that have been collected in a loop detector was the lowest Therefore, creating a traffic volume of representative value, we proposed a method to use loop detector than the average traffic volume collected by each detector. It shows that it is more important to use one high-quality data rather than various low-quality data to produce a representative value.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.59-88
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• 1996

This study has determined optimal type, and location of loop detector to measure accurately traffic condition influenced by traffic variation with real time. Optimal type of loop detector for through vehicle at stop bar was determined by confidences of occupancy period, and nonoccupancy period, and so appropriate detector type for application to real time traffic control system has been decided on special loop detector.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.91-125
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• 1996

The purpose of this paper is comparatively to evaluate the confidence of Vehicle-Detector informations for various detectors in order to test to be possible the application of these to real time traffic signal control. The detectors which are tested for this study are Circle-Shaped Loop, Ultrasonic, Microwave and Image detector. The tested items for each detectors are traffic volume, degree of saturation for through and left turn movement, speed and queue length, etc. These items for each are tested at the field according to several situations, such as dry day, raining day, night and daytime. The result of these tests are performed comparative analysis and statistical examination in order to increase the confidence of the experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.671-680
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• 2016

This research suggested a new real-time traffic signal control algorithm using fusion data of the travel time and the occupancy rate. This research applied the travel time data of traffic information system to traffic signal operation, and developed the signal control process using the degree of saturation that was estimated from the travel time data. This algorithm estimates a queue length from the travel time based on a deterministic delay model, and includes the process to change from the queue length to the degree of saturation. In addition, this model can calculate the traffic signal timings using fusion data of the travel time and the occupancy rate based on the saturation degree. The micro simulation analysis was conducted for effectiveness evaluation. We checked that the average delay decreased by up to 27 percent. In addition, we checked that this signal control algorithm could respond to a traffic condition of oversaturation and detector breakdown effectively and usefully. This research has important contribution to apply the traffic information system to traffic signal operation sectors.