A Set of New Traffic-responsive Ramp-metering Algorithms and Microscopic Simulation Results

In this paper, we present a novel switching traffic-responsive ramp-metering controller that adapts to the different traffic dynamics under different congestion conditions—free-flow or congested. The approach of multirate linear quadratic control with integral action (LQI) is employed to compensate for disturbances and to accommodate the difference between the model sampling time and the metering-rate update interval. In addition, a queue length regulator is designed to prevent the queue from exceeding the ramp storage capacity and yield improved performance over the currently used ad hoc “queue-override” scheme. Subsequently, a queue length estimator is designed to provide feedback to the queue length regulator, using the queue-detector speed data that are available in the field. A local ramp-metering control strategy is proposed to achieve the control goal of reducing the spatial and temporal span of the congestion, while satisfying the on-ramp storage capacity constraints, using locally available information. Test results on a calibrated microscopic traffic simulator demonstrate the performance and effectiveness of the switching ramp-metering controller, the queue length estimator and regulator, and the overall control strategy. The Total Vehicle and Passenger Congestion Delays are both reduced by 16%, while the Total Travel Time is improved by 5.6%. As a comparison, simulation results of ALINEA are also presented.