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A Network Based Model for Traffic Sensor Location with Implications on O/D Matrix Estimates

机译:基于网络的交通传感器定位模型,对O / D矩阵估计有影响

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摘要

In this paper, we define and solve the sensor location problem(SLP), that is, we look for the minimum number and location of counting points in order to infer all traffic flows in a transport network. We set up a couple of greedy heuristics that find lower and upper bounds on the number of sensors for a set of randomly generated networks. We prove that solving the SLP implies that the Origin/Destination(O/D)matrix estimation error be always bounded.
机译:在本文中,我们定义并解决了传感器位置问题(SLP),即,我们寻找计数点的最小数量和位置,以便推断传输网络中的所有流量。我们建立了几个贪婪的启发式方法,它们为一组随机生成的网络确定了传感器数量的上限和下限。我们证明解决SLP意味着Origin / Destination(O / D)矩阵估计误差总是有界的。

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