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Freeway ramp control has been successfully implemented since mid 60's, as an efficient and viable freeway management strategy. However, the effectiveness of any ramp control strategy is largely dependent on optimum parameter values which are preferably determined prior to deployment. This is certainly the case happening to the current Stratified Zone Metering (SZM) strategy deployed in the 260 miles freeway network of Minneapolis - St. Paul metropolitan area. In order to improve the performance of the SZM, which highly depends on the values of more than 20 parameters, this research first proposed a general methodology for site-specific performance optimization of ramp control strategies using a microscopic simulation environment, as an alternative to trial and error field experimentation, and implemented the methodology to the SZM. The testing results show that the new SZM control with site-specific optimum parameter values significantly improves the performance of freeway system compared with the original SZM strategy. Secondly, this research proposed a methodology to explore the common optimum parameter values for the current SZM strategy for the whole Twin Cities freeway system, in order to replace the site-specific optimum values which have minor practical value because of the difficulties in implementation and numerous time-consumption to search the site-specific optimum values for all the freeway sections. The common parameter values are identified applying the Response Surface Methodology (RSM) based on 4 specifically selected freeway sections which can represent all types of freeway sections in Minneapolis-St. Paul metropolitan area.

Data collection and performance measurement for signalized arterial roads is an area of emerging focus in the United States. As indicated by the results of the 2005 Traffic Signal Operation Self-Assessment Survey, a majority of agencies involved in the operation and maintenance of traffic signal systems do not monitor or archive traffic system performance and thus have limited means to improve their operation. With support from the Transportation Department of Hennepin County, Minneapolis, MN, a system for high resolution traffic signal data collection and arterial performance measurement has been successfully built. The system, named SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic Signals), is able to collect and archive event-based traffic signal data simultaneously at multiple intersections. Using the event-based traffic data, SMART-SIGNAL can generate timedependent performance measures for both individual intersections and arterials including intersection queue length and arterial travel time. The SMART-SIGNAL system has been deployed at an 11-intersection corridor along France Avenue in south Minneapolis and the estimated performance measures for both intersection queue length and arterial travel times are highly consistent with the observed data.

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.