Title | A sampling theorem approach to traffic sensor optimization |
Publication Type | Journal Article |
Year of Publication | 2008 |
Authors | Ni D, Leow W.L., Pishro-Nik H |
Journal | IEEE Transactions on Intelligent Transportation Systems |
Volume | 9 |
Issue | 2 |
Start Page | 369 |
Pagination | 369 - 374 |
Date Published | 06/2008 |
ISSN | 1524-9050 |
Accession Number | 10034937 |
Keywords | Sampling theorem, sensor optimization, spectral domain analysis, Traffic congestion, traffic sensing |
Abstract | 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. |
DOI | 10.1109/TITS.2008.922925 |