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Optimal Locations of License Plate Recognition to Enhance the Origin-Destination Matrix Estimation

机译:车牌识别的最佳位置,以增强起点-终点矩阵估计

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This paper develops a model to determine and to locate the optimal numbers of license plate recognition (LPR) to minimize error rates of O-D matrix estimation, percentages of LPR coverage (a proxy of installation cost), and percentages of recorded trips (a proxy of privacy invasion). A genetic algorithm is proposed to solve the combinatorial problem. To demonstrate the applicability of the proposed model and solving algorithm, two exemplified cases and a real-world case are investigated. The results have consistently showed that the optimal locations of LPR are at both ends and in the middle of the segments of a freeway corridor with heavy link traffics. If an extensive coverage of LPR is attempted, however, additional LPR may be placed at the segments with light link traffics so as to balance out the privacy invasion.
机译:本文开发了一个模型,用于确定和定位最佳车牌识别(LPR)数,以最大程度地减少OD矩阵估计的错误率,LPR覆盖率的百分比(安装成本的代理)和记录的行程的百分比(代理的费用)。隐私入侵)。提出了一种遗传算法来解决组合问题。为了证明所提出的模型和求解算法的适用性,研究了两个示例案例和一个实际案例。结果一致表明,LPR的最佳位置是在交通繁忙的高速公路走廊的两端和中间。但是,如果尝试广泛覆盖LPR,则可以在光链路流量较小的路段上放置其他LPR,以平衡隐私的入侵。

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