Iterative learning control approach for ramp metering

An iterative learning control scheme is developed to the traffic densitycontrol in a macroscopic level freeway environment. With rigorous analysis, the proposed intelligentcontrol scheme guarantees the asymptotic convergence of the traffic density to the desired one. Thecontrol scheme is applied to a freeway model, and simulation results confirm the efficacy of theproposed approach.

Double-layer ramp-metering model for incident congestion on expressway

In order to ensure stable traffic capacity and avoid incident congestion, a double-layer ramp metering model is proposed in this paper, based on coordination control theory, to predict and control the traffic flow at each on-ramp, when there is incident congestion on the expressway. The function of the lower model is to recognize where the incident congestion exists, based on an adaptive neural net- work with inputs of traffic flow, velocity and density. The outputs of the lower model are the number of section where the congestion occurs, the number of ramp which should be controlled, and real-time traffic flow information. These outputs should be transmitted to the upper model. The function of the upper model is to design the ramp-metering strategy based on nonlinear theory. The outputs of the up- per model are a ramp-metering rate and traffic-flow state after ramp controlling on the expressway. The results of the simulation show that the double-layer ramp metering model could shorten the delay by about 25%, and the variance of the model results is 0. 002, which could certify the control strategy is equitable.

A simulation study of using active traffic management strategies on congested freeways

The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were selected to evaluate the impacts of ATM such as speed harmonization, shoulder utilization, and ramp metering. Test beds used in this study were at places where an ATM is either proposed or previously implemented, i.e., where data exists for condi- tions prior to and after the implementation of ATM. Data collected from the test beds were used in a simulation model to evaluate the impacts of each ATM strategy on speed, travel time, and crash rates. Simulation results indicated that the implementation of speed harmonization on US 90 showed a 14% reduction in crashes and a 2%-3% increase in freeway speed; the implementation of hard shoulders on US 90 showed a 39% increase in travel time, 22% increase in freeway capacity and 60% decrease in delays; and the implementation of ramp metering on US 59 between Bissonnet St. and Fondern road showed a decrease of 23 % in freeway travel time, a 14% increase in freeway speed and 11% decrease in accident rates.

Integrated control of highway traffic flow

Several efforts have been made during recent years on the control of traffic flow using ramp metering,variable speed limit and lane change control.Most of these techniques reported significant traffic mobility improvements in macroscopic simulations,which cannot be confirmed in some microscopic simulation cases.We demonstrate that the lack of travel time improvement is due to the forced lane changes at the bottleneck which introduce a capacity drop.In this paper,a lane change controller is proposed which provides lane change recommendations to avoid the capacity drop.Combined with the lane change control,a feedback linearisation variable speed limit controller which maintains the bottleneck flow at the maximum level and coordinates with ramp metering controllers is proposed.The integrated VSL,RM and LC controller can improve system performance,manage the ramp queues and maintain the fairness between mainline and on-ramp flows.Microscopic simulations show consistent improvements under different scenarios.