The Investigation Of Intelligent Control Approaches For Freeway On-Ramp Metering

In rescent years the phenomena of traffic congestion on urban freeways is becoming more and more familiar due to the dramatic expansion of car-ownership, which makes it urgent and significant to apply efficient control approaches to keep the traffic condition in an ideal way. On-ramp metering, when properly applied, is considered as an efficient traffic management tool for freeways. A research on intelligent freeway on-ramp metering approaches was conducted according to some characteristics of the freeway traffic state. The main contents and results are as follows:According to the repeatability of the traffic pattern for freeway, iterative learning approach (ILC, in short) method was applied to regulate the congestion state. A one order open-closed loop ILC scheme was designed to control the traffic density. By means of rigorous theoretic analysis, its validity and superiority are adequately proved. Simulation results validate its efficiency. When compared to the conventional open loop ILC approach, the strategy proposed in this thesis has faster convergence speed and better transient performance than the open loop ILC law.Based on the one order open-closed ILC approach, a high order open-closed loop ILC scheme was further analyzed and designed. This approach does not only have the advantages as the first order one, but also makes the entire freeway system more stable as it collects more system information to design the metering rate. Simulation results confirmed its efficiency. When compared to the well-known ALINEA approach, this high order open-closed loop ILC approach has faster convergence speed and better robust performance.According to the problems that are encountered in current ramp control research: uncertainty of the traffic model,difficulty in designing an adaptive ramp controller and the necessary of the coordinated algorithms, the neuro-fuzzy network method was applied to resolve the problems above and an adaptive and coordinated on-ramp strategy was designed. This approach considers both the traffic density and the on-ramp queue length together and aims at controlling both of them simultaneously. When compared to the well-known ALINEA strategy, this approach has better performance in restraining traffic flow fluctuation and queue increase. It is worthy to point out that the approach is coordinated, which can utilize the road capacity better than the single on-ramp methods.