IDENTIFICATION OF NETWORK SENSOR LOCATIONS FOR TRAFFIC FLOW ESTIMATION

摘要

This paper deals with the network sensor location problem (NSLP) for identifying the set of sensor locations that minimizes the variability of traffic flow estimation given a budget constraint. The trace of the covariance matrix is adopted as a measure of traffic flow variability. Based on the trace of the covariance matrix of the posterior traffic flow estimation conditional on a given set of sensor locations, the general form of the NSLP is derived. For illustration purposes, the multivariate normal distribution for the prior traffic flow estimation is assumed. In this case, the actual value of the counted flows is not required. Furthermore, an incremental method, which can avoid matrix inversion and give priorities of the identified sensor locations, is presented to solve the NSLP. Finally, a numerical example based on the Nguyen–Dupuis network is given to illustrate the NSLP approach and clarify some of its implementation details.