Development and Evaluation of Online Estimation Methods for Feedback-Based Freeway Ramp Metering Strategy

Critical density of a freeway link is subject to changes over time due to circumstances such as environmental conditions (snow, rain, etc.), traffic incidents. Because of its impacts on the performance of some ramp metering strategies that make use of critical density as a threshold value for control action, it is necessary to trace the real value of the critical density. Hence, methodologies for the on-line estimation of critical density using Extended Kalman Filtering (EKF) and Kalman Filtering (KF) were proposed in this paper. Basically, critical density was chosen as the state variable to be determined using system output, measurement of traffic flow on the downstream freeway link. Then, these methods are evaluated using microscopic simulation environment, PARAMICS. The results indicate that both methods (using KF and EKF) provide better performance in terms of tracing time-dependent changes of real critical occupancy effectively for all the scenarios tested compared with the case where constant critical occupancy used.