In urban transportation network, generally, traffic sensors are unable to fully cover the freeway network, and only local measurement data is available. To accurately and timely estimate traffic density in an urban freeway network, 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 using the cell transmission model (CTM). Secondly, based on the model, a distributed observer is designed, which gains are computed by using LMI technique according to the Lyapunov function and S-procedure theory. Thus, the traffic densities of the whole network can be estimated by the distributed observer. This method was applied to Beijing third ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.
Traffic Density Estimation of Urban Freeway by Dynamic Model Based Distributed State Observer
17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China
CICTP 2017 ; 603-612
2018-01-18
Aufsatz (Konferenz)
Elektronische Ressource
Englisch