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首页> 外文期刊>Transportation Research Part B: Methodological >A network sensor location procedure accounting for o-d matrix estimate variability
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A network sensor location procedure accounting for o-d matrix estimate variability

机译：考虑o-d矩阵估计变异性的网络传感器定位过程

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摘要

The paper illustrates an innovative and theoretically founded methodology for solving the network sensor location problem (NSLP), explicitly accounting for the variability of the o-d matrix estimate. The proposed approach is based on a specific measure, termed synthetic dispersion measure (SDM), related to the trace of the covariance matrix of the posterior demand estimate conditional upon a set of sensor locations. Under the mild assumption of multivariate normal distribution for the prior demand estimate, the proposed SDM does not depend on the specific values of the counted flows - unknown in the planning stage -but just on the locations of such sensors. From a practical standpoint, a stepwise algorithm is implemented for calculating the proposed measure given a set of link counts, which avoids matrix inversion. In addition, a sequential heuristic algorithm is presented for the application of the proposed NSLP to real contexts. The methodology also allows a formal budget allocation problem to be set between surveys and counts in the planning stage, in order to maximize the overall quality of the demand estimation process.
机译：本文说明了解决网络传感器位置问题（NSLP）的创新方法，并在理论上建立了方法，明确说明了o-d矩阵估计的可变性。所提出的方法基于一种称为合成色散度量（SDM）的特定度量，该度量与基于一组传感器位置的后需求估算的协方差矩阵的轨迹有关。在先验需求估算的多元正态分布的温和假设下，建议的SDM并不取决于计算流量的特定值（在规划阶段未知），而仅取决于此类传感器的位置。从实际的角度来看，在给定一组链路计数的情况下，采用逐步算法来计算建议的度量，从而避免了矩阵求逆。此外，提出了一种顺序启发式算法，用于将拟议的NSLP应用到实际环境中。该方法还允许在计划阶段在调查和计数之间设置正式的预算分配问题，以使需求估计过程的整体质量最大化。

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