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Lane-based queue length estimation at signalized intersections using single-section license plate recognition data
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DOI：10.1080/21680566.2021.1991504.png)
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摘要
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Due to full record of discharging vehicle headway, License Plate Recognition (LPR) is used as an ideal source in most existing queue length estimation methods through a double-section detection using shock-wave models or input-output models. However, the impacts of heavy vehicles and miss detection by LPR detectors are mostly ignored. Therefore, this paper proposes a lane-based queue length estimation method using single-section LPR detection, considering miss detection and heavy vehicles. The queue length estimation problem is transformed to a change-point identification problem for discharging headways time-series, using E-Divisive with Medians (EDM) method. The maximal queue length is identified as the change-point of the discharging headways with the maximal differences between queued and non-queued vehicles, considering the queuing homogeneity of a lane group and the miss detection rate of LPR. The proposed method is validated using simulation and empirical cases with promising performance and good robustness under various conditions.
Keyword:
Signalized intersection
queue length
license plate recognition data
miss detection
E-Divisive with medians
期刊
IF:
3.4
论文数:
564
被引数:
1.2K
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