Single-sensor based nonlinear density estimation for traffic networks with multiple routes and sections

A single origin and single destination traffic network with multiple routes and sections is considered. The state variables are assumed to be traffic densities in these sections. For dynamic routing of traffic, accurate measurement of these variables is needed. This requires the placement of numerous sensors, one at each section, which is a costly solution. In this work, a simpler solution is presented based on a single sensor placed at the destination node and the use of an extended Kalman filter for estimation of traffic densities in individual route sections. Two sets of simulations are provided for illustration.