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

Abstract

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.