A Sampling Theorem Approach to Traffic Sensor Optimization

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 NextGeneration 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 determi...

• Type: Journal
• Year: 2008
• Where: TITS
• Authors: Woei Ling Leow, Daiheng Ni, Hossein Pishro-Nik
• Keywords: Characterization Curve, Field Data, Sensor, TITS 2008