• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.489-498
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• 2006

In this paper, we suggested a vehicle classification algorithm using pattern recognition method. At present, Inductive Loop Detector is rarely used for vehicle classification because of its low accuracy. To improve the accuracy, we suggest a new algorithm for Loop Detector using neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and occupancy-time. The output is classified vehicles. The developed algorithm was assessed at test sites and the recognition rate was 91.3percent. The results verified that the proposed algorithm improves the vehicle classification accuracy compared to the conventional method based on Loop Detector.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.353-359
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• 2006

Image frame analysis is a conventional way of evaluating loop detector's performance. In image frame analysis, the time to evaluate performance is linearly proportional to the number of evaluated subjects, and the results can be subjective, depending on operator's personal evaluation standards and physical condition. Also, this method is often inferior in accuracy to that provided by the evaluated devices. Therefore, it is critical to develop a portable standard system which has better accuracy and more objectivity in evaluating vehicle detectors. This paper discusses function and reliability of tape-switch detector, which can be a replacement for image frame analysis, for effectively measuring traffic volume, speed, and occupancy.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.123-134
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• 2005

This research aims at developing a new method which can replace the existing method. known as the quality factor(Q factor) method by an L-R-C test for use in the performance test of inductive loop detectors(ILD) being installed and maintained. In this study, a sensor to detect a magnetic field in terms of frequency and intensity, a method to collect field data, the method of analysis, and the method of diagnosis were developed. An automatic diagnosis system which was developed to overcome those drawbacks has the following features : First, field data is collected automatically by a test vehicle equipped with magnetic field sensors that is running can be said to along the roadway and. thus, the new system completely overcome the roadway and, thus, the new system can be said to completely overcome the inefficiency of the existing method second, since the magnetic fold generated from the ILD is the final output of the whole system of ILD, the existing problem has been solved. third. since each of the detection area by height is collected by the magnetic sensors installed by height. a basic for the identification of the vehicle types to be detectable and the setting of adjustment factors has been made. For the automatic diagnosis system developed during in this study, a reliability test was carried out by comparing vehicle times of ILD installed ideally.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.163-174
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• 2002

Speeding has been reported as one of the major causes for fatal traffic accidents in Korea. The resolution against this dangerous speeding comes to make the automated speed enforcement system an enforcement tool. The speed detection device, which measures speeds of each incoming vehicles using double loop sensors, requires high accuracy. The object of this study is to develop an accurate speed measurement algorithm using double loop detectors. Some important findings are summarized as follows: 1) It was found that speed measurement errors are caused by scanning rate, distance of two loops, irregular vehicle trajectories, multiple vehicles in detection zone. 2) A proposed algorithm using two signal set proved to reduce variance as well as mean of speed measurement. 3) A proposed filtering algorithm was effective to filter irregular driving vehicles and multiple vehicles in detection zone. A comprehensive field test of developed algorithm resulted in significant improvement of speed measurement accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.112-125
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• 2019

An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s.

• 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 Korean Society of Transportation
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• v.26 no.4
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• pp.229-239
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• 2008

Most algorithms for detecting incidents have been developed under the premise that congestion must happen whenever an incident occurs. For that reason, the performance of these algorithms could not be guaranteed in cases where congestion did not happen due to traffic operations with low flows despite the occurrence of an incident. The objective of this paper is to develop an automatic incident detection algorithm using a new diagram that can reliably detect the incident under various conditions of traffic operations including a low volume state. Compared with the McMaster Algorithm, the proposed algorithm in this paper was evaluated with three different cases in which the incidents occur in traffic operations with a low volume state, a relatively high volume state, and a recurrent congestion state. It is shown that the new algorithm has a capability to identify the flow characteristics of incidents for all the three cases and is much better than McMaster algorithm in terms of detection rate and false alarm rate.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.71-83
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• 2001

This paper introduces the simulation system which was developed to evaluate the effectiveness of ITS, and presents its adaptabilities to traffic signal control systems. The simulation system in this paper has a function of real-time testing and evaluating traffic control systems. It consists of Modu-RE which is a simulation operating software and Real-CID which is a controller interface device. Real-CID allows Modu-RE to communicate with traffic control hardware.

• Journal of Korean Society of Transportation
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• v.15 no.4
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• pp.53-71
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• 1997

This paper presents a methodology for estimating average travel speed using volume and occupancy data from single magnetic loop detectors for signalized arterials. Three methods were developed and evaluated using field data: VPLUSKO method, fuzzy control method, and neural network method. While the VPLUSKO method is easy to apply, it results poor performances compared to other methods. The neural network method showed the best performances among the candidate methods. This method revealed the weakness in transferability, however. From limited cases of field test, it was concluded that the method of the fuzzy control application showed reasonable performance of estimation. It was also demonstrated that the fuzzy control method has the capability of transferability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.13-23
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• 2016

Many traffic centers are highly hesitant in employing existing Automatic Incident Detection Algorithms due to high false alarm rate, low detection rate, and enormous effort taken in maintaining algorithm parameters, together with complex algorithm structure and filtering/smoothing process. Concerns grow over the situation particularly in Freeway Incident Management Area This study proposes a new algorithm and introduces a novel concept, the Displaced Flow Index (DiFI) which is similar to a product of relative speed and relative occupancy for every execution period. The algorithm structure is very simple, also easy to understand with minimum parameters, and could use raw data without any additional pre-processing. To evaluate the performance of the DiFI algorithm, validation test on the algorithm has been conducted using detector data taken from Naebu Expressway in Seoul and following transferability tests with Gyeongbu Expressway detector data. Performance test has utilized many indices such as DR, FAR, MTTD (Mean Time To Detect), CR (Classification Rate), CI (Composite Index) and PI (Performance Index). It was found that the DR is up to 100%, the MTTD is a little over 1.0 minutes, and the FAR is as low as 2.99%. This newly designed algorithm seems promising and outperformed SAO and most popular AIDAs such as APID and DELOS, and showed the best performance in every category.