• International Journal of Highway Engineering
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• v.14 no.2
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• pp.165-174
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• 2012

In this study, a method for evaluating the performance of speed measurements was developed to assess the qualities of a vehicle detector. The evaluation method considers measurement errors that are reflected in a reference speed. For this, the concept of uncertainty in measurement was applied to the development method. Other factors such as precedent study, statistical processing techniques, and speed measurement performance method of traffic enforcement equipment and vehicle detection systems were also reviewed. Through this process, the problems of the existing evaluation methods were derived and developed for the new performance evaluation method. Vehicle detectors that are installed in the field were evaluated using the traditional assessment methods and the developed method. As a result, for traditional assessment methods, it was found that evaluation criteria are acceptable, while developed method's criteria are not acceptable. This means that traditional assessment methods do not sufficiently consider errors in measurement, so it has potential to over-estimate for performance of evaluation equipment. On the other hand, it was represented that the developed method should include variable factor such as errors in measurement and more precise compared to traditional assessment methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.105-115
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• 2017

Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.11-19
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• 2000

Real-time extraction of traffic information such as the number of vehicles passing, speed, road-occupancy rate, distance between vehicles, and vehicle types from the traffic scenes acquired from the camera on the road, is a core component of the intelligent transportation system(lTS) We present a scheme of extracting the traffic informations based on the spatio-temporal image analysis, which is robust to the variation of weather conditions and the shades. The images of two detection regions for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shade, using the statistical and structural features Quantitative traffic informations are retrieved by analysing the two spatio-temporal images. Since only the local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized while ensuring the detection performance robust to the operating condition.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.113-124
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• 2009

This paper suggests a new approach for providing information for driver safety at signalized intersections. Particularly dangerous situations at signalized intersections such as red-light violations, accelerating through yellow intervals, red-light running, and stopping abruptly due to the dilemma zone problem are considered in this study. This paper presents the development of a dangerous vehicle determination algorithm by collecting real-time vehicle speeds and times from multiple point detectors when the vehicles are traveling during phase-change. For an evaluation of this algorithm, VISSIM is used to perform a real-time multiple detection situation by changing the input data such as various inflow-volume, design speed change, driver perception, and response time. As a result the correct-classification rate is approximately 98.5% and the prediction rate of the algorithm is approximately 88.5%. This paper shows the sensitivity results by changing the input data. This result showed that the new approach can be used to improve safety for signalized intersections.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.95-100
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• 2013

Smart surveillance, is the use of automatic video analysis technologies in video surveillance applications. We present a robust object tracking method using pan-tilt-zoom camera for intelligent surveillance System, As the result of the experiment using 78 vehicle, the success rate of the tracking for moving object & non-moving object werw 97.4% and 91%. and 84.6%. the success rate o PTZ control for license plate image.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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• pp.65-70
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• 2008

Smart surveillance, is the use of automatic video analysis technologies in video surveillance applications. We present a robust object tracking method using pan-tilt-zoom camera for intelligent surveillance System, As the result of the experiment using 78 vehicle, the success rate of the tracking for moving object & non-moving object werw 97.4% and 91%. and 84.6%. the success rate o PTZ control for license plate image.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.9-18
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• 2004

This paper presents a vehicle detecting algorithm using microwave system signals. The Proposed algerian decides the breakpoint of signals using the likelihood criteria. The decided signals are segmented and simplified. The proposed searching algorithm uses the Euclid distance from the weighted signal data. We tested the proposed algorithm to compare with the segmentation which is a method using smoothing and edge detection. We confirm that the proposed algorithm is very useful for detecting vehicles by field test.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.13-22
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• 2009

Recently, DSRC technology is used in the various fields such as parking system, BIS, ETC, etc. This paper suggests a traffic information system using this DSRC technology. The traffic information processing based on point detection using existing vehicle detection equipment is the system in which a collection and a service are operated separately while the traffic information system based on the link detection using DSRC is able to collect and provide the traffic information through the communication between RSE and OBU. The speed of a traffic congestion is high on the process converted from a point passing speed to a link average speed because the vehicle detection equipment makes the link traffic information into the point information. When the condition of traffic is deteriorated, traffic speed of the vehicle detection equipment becomes higher than DSRC. Especially, in this system, deflection by data of the traffic speed of the traffic information system is much decreased, and the unexpected condition detection and traffic condition are provided promptly.