With the advent of intelligent transportation systems, transportation networks have a considerable amount of traffic detectors, and large amounts of streaming data are available to manage and plan a multi-modal network and provide real-time traffic information to travelers. The related problem of optimally locating sensors on the network to estimate flows has been the object of growing interest in the past few years. Available sensors use various technologies and measure different aspects of traffic flows. This paper classifies sensor location problems in the literature in two categories: the sensor location flow-observability problem and the sensor location flow-estimation problem. This paper reviews the existing contributions for the latter of the two problem types and presents a unifying bilevel optimization framework in which the upper level addresses the location decisions and the lower level addresses the estimation variables. Several directions for future research are discussed.
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