Title :
Simultaneous traffic count and ramp flow estimation for multilane freeways based on Markov models
Author :
Yong Ma ; Liguo Zhang ; Lu Zhang
Author_Institution :
Sch. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing, China
Abstract :
As a distributed parameter system, traffic flow model of freeway traffic is determined by the traffic state on-road and boundary flows form on-ramp or off-ramp sections. The existing studies for traffic estimation mainly focus on the traffic parameter, namely density (or vehicles) of mainline traffic. In this paper, Kalman filtering for simultaneous traffic counts and off-ramp flow estimation is proposed with the linearization of the speed density observation equation. The state-space model is formulated by using a Markov chain to describe the vehicles´ lane-change movements. Numerical studies are carried out to investigate the performance of the developed approach.
Keywords :
Kalman filters; Markov processes; distributed parameter systems; road traffic; road vehicles; state-space methods; Kalman filtering; Markov chain; Markov models; boundary flows; distributed parameter system; mainline traffic density; multilane freeway traffic; off-ramp flow estimation; off-ramp sections; on-ramp sections; ramp flow estimation; speed density observation equation; state-space model; traffic count estimation; traffic flow model; traffic parameter; traffic state on-road flows; vehicle lane-change movements; Equations; Estimation; Kalman filters; Mathematical model; Traffic control; Vectors; Vehicles; Kalman filtering; Markov model; Off-ramp flow; Simultaneous input and state estimation; Traffic counts;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6560934
