Yorgos Stephanedes, Former University Researcher, Civil Engineering
Optimal management of freeway congestion requires a hierarchical, integrated approach involving prediction of future traffic conditions, determination of optimal control solutions for the predicted traffic conditions and on-line adjustments of the prediction-based control solutions. In the previous phase of this research a computer-based control-emulation method that can evaluate various automatic rate-selection strategies has been developed. Further, an optimization method that can determine the best set of metering thresholds for a given section of freeway was also developed. The optimization method was applied to a section of the I-494 freeway and the resulting thresholds were implemented in the field. This project develops enhanced rate-selection metering strategies using additional traffic information that can be measured with current detection systems. The control-simulation software will also be enhanced to handle larger freeway zones and long freeway sections. The optimization method will be extended, automated and incorporated into the control-simulation software. Finally, predictive control methods will be studied. As the result of this research, a prototype software implementing on-line ramp metering control strategies will be developed.