Distributed state-observer-based traffic density estimation of urban freeway network

In order to accurately and timely estimate traffic densities in a large-scale urban freeway network when traffic sensors do not completely cover the whole freeway network and thus only local measurement data can be utilized, this paper proposes a distributed state observer approach based on a macroscopic traffic flow model. Firstly, the urban freeway network is modeled in the way of distributed systems by combining the cell transmission model (CTM) with the dynamic graph hybrid automata (DGHA), and a Piece Affine Linear System (PWALS) is deduced. Furthermore, based on the PWALS model, a switched and distributed state observer is designed to estimate traffic densities of the freeway network, where a set of gain matrices for the observer are computed by using LMI technique with the help of the S-procedure theory. Finally, the PWALS model and the corresponding distributed observer are utilized to Beijing second ring freeway, and the experimental results demonstrate the effectiveness and applicability of the proposed approach.