Employment of the Traffic Management Lab for the Evaluation and Improvement of Stratified Metering Algorithm - Phase III

Abstract

The evaluation results (done in Phase II) demonstrated that the SZM strategy was generally beneficial. However, they also revealed that freeway performance degraded by reducing the ramp delays. Therefore, it is desired to improve the effectiveness of the current SZM control. There are two objectives in this study. One objective is to improve the control logic of current SZM strategy. This is accomplished through an estimation algorithm for the refined minimum release rate. The simulation results indicate that the improved SZM strategy is very effective in postponing and decreasing freeway congestion while resulting in smoother freeway traffic flow compared to the SZM strategy. The second objective of this project is to improve the current queue size estimation. Depending on the counting error of queue and passage detectors, freeway ramps are classified into three different categories, and different methods are applied respectively for improved queue size estimation. The surveillance video data were recorded and used to verify the improvement of the proposed methods. The results indicate that the proposed methods can greatly improve the accuracy of queue size estimation compared with the current methodology. Also, the proposed method was evaluated by the micro-simulation. The simulation results indicate the performance of freeway mainline is significantly improved. And the total system performance is better than the original SZM control.