ABSTRACT
Speed detection in traffic networks is easy to access and measure with the development of ubiquitous sensing technologies. This chapter presents a consensus-based decentralized extended Kalman Filter (EKF) for real-time traffic parameter estimation of large-scale freeway networks with speed measurement. Real-time knowledge about traffic conditions of urban road transportation systems is critical for traffic management and control. There are many well-established technologies for collecting vehicle speed and flux data, including loop detectors and automatic vehicle identification (AVI) sensors. Road traffic estimation includes both traveling time estimate and traffic parameter estimate for any origin–destination pair of networks. The chapter presents Godunov scheme for discretization of the Lighthill–Whitham–Richards (LWR) model. It formulates consensus-based decentralized EKF for the large-scale freeway networks. The chapter explains a five-mile freeway of Interstate 80 East (I-80E) in Alameda, Northern California to investigate the performance of the developed approach.
