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A network based model for traffic sensor location with implications on O/D matrix estimates. (English) Zbl 1069.90503

Summary: 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. With respect to alternative sensor location strategies, simulation experiments show that: (i) measurement costs being equal, the O/D estimation error is lower, and (ii) conversely, O/D estimation error being equal, the number of sensors is smaller.

MSC:

90B10 Deterministic network models in operations research
90B20 Traffic problems in operations research
90B80 Discrete location and assignment
90C59 Approximation methods and heuristics in mathematical programming
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