Reference:
A. Hegyi,
D. Girimonte,
R. Babuska, and
B. De Schutter,
"A comparison of filter configurations for freeway traffic state
estimation," Proceedings of the 2006 IEEE Intelligent
Transportation Systems Conference (ITSC 2006), Toronto, Canada,
pp. 1029-1034, Sept. 2006.
Abstract:
We present a comparison for several filter configurations for freeway
traffic state estimation. Since the environmental conditions on a
freeway may change over time (e.g., changing weather conditions),
parameter estimation is also considered. We compare the performance of
the extended Kalman filter and the unscented Kalman filter for state
estimation, parameter estimation, joint estimation and dual
estimation. Furthermore, the performance is evaluated for different
detector configurations.
The main conclusions from the simulations are that (1) the performance
of the extended Kalman filter and the unscented Kalman filter is
comparable, (2) joint filtering performs significantly better than
dual filtering, and (3) a larger number of detectors results in better
state estimation, but has no significant influence on the parameter
estimation error.