Link Flow Estimation in Traffic Networks on the Basis of Link Flow Observations

Abstract

Given a traffic network, the problem of identifying the smallest subset of links on which to locate sensors that allow the exact estimation of a given subset of links flows is dealt with, and methods for solving this partial link-observability problem are given. As sources of information, the authors consider 2 separate types of link sensors: counters and scanners. The first type leads to a method, which is an alternative to the previous method of Hu, Peeta, and Chu. First, the authors show how the previous method can be directly used for solving the partial observability problem. Next, the authors present a simple alternative algorithm, based on the pivoting strategy, that can include information about route and Origin-Destination (OD) flows observability. The observability problem based on scanners leads to a more difficult problem but supplies much more information about traffic flows. The authors give 2 simple algorithms for solving this problem in this case. The first algorithm allows checking that a given subset of links supplies the required information to estimate the flows in the selected subset of links, and provides information about route and OD observability. The second, which is a random algorithm, permits reducing the number of links of an initial subset of scanned links that solves the problem, and when a further reduction is not possible, modifies the initial set of scanning links for a new trial randomly. The proposed methods are illustrated using the parallel highway network of Hu, Peeta, and Chu. Last, the authors apply methods to two examples of applications—the Nguyen-Dupuis and the real Cuenca network—and provide some conclusions.