A Sampling Theorem Approach to Traffic Sensor Optimization
Leow, W.L.; Daiheng Ni; Pishro-Nik, H.
Intelligent Transportation Systems, IEEE Transactions on
Volume 9, Issue 2, June 2008 Page(s):369 - 374
Digital Object Identifier 10.1109/TITS.2008.922925
Summary:With the objective of minimizing the total cost, which includes both sensor and congestion costs, the authors adopted a novel sampling theorem approach to address the problem of sensor spacing optimization. This paper presents the analysis and modeling of the power spectral density of traffic information as a 2-D stochastic signal using highly detailed field data. The field data were captured by the next-generation simulation (NGSIM) program in 2005. To the best knowledge of the authors, field data with such a level of detail were previously unavailable. The resulting model enables the derivation of a characterization curve that relates sensor error to sensor spacing. The characterization curve, concurring in general with observations of a previous work, provides much more detail to facilitate sensor deployment. Based on the characterization curve and a formulation relating sensor error to congestion cost, the optimal sensor spacing that minimizes the total cost can be determined.
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