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This characteristic of the wavelet technique was used in developing the wavelet incident detection algorithm in this study.
The test results indicate that the wavelet incident detection algorithm performs better than other algorithms, demonstrating its potential for practical application.
A real-time traffic incident detection algorithm is proposed and applied to the monitoring of a complex road junction in the city of Nancy in France.
Off-line tests were conducted to substantiate the performance of the proposed incident detection algorithm based on simulated data generated employing the calibrated INTRAS simulation model and on real incident data collected on the I-880 freeway in Oakland, California.
Unlike the existing wavelet incident detection algorithm, where the wavelet technique is utilized to denoise data before the data is input into an algorithm, this paper presents a different approach in the application of the wavelet technique to incident detection.
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Even though incident detection algorithms are designed and implemented for quickly detecting incidents, the criterion of mean detection delay has hardly been well defined and utilized in developing and evaluating incident detection algorithms.
Selected incident detection algorithms were also compared with the CUSUM algorithms.
SVMs are usually employed for incident detection algorithms identifying the anomalies of traffic flow model using single or two sensors [31].
In addition, most incident detection algorithms do not have an optimal property in terms of detection delay with respect to false alarm rate.
This paper reports the intensive test of the new transport systems centre (TSC) algorithm applied to incident detection on freeways.
To implement the algorithm, called the CUSUM algorithm that was derived from the optimization formulation of the incident detection problem, a simplified procedure was developed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com