Abstract
Parameters concerning real-time, advanced traffic-control systems must be appropriately set for realizing adequate performance in urban areas that demonstrate fluctuating and dynamic traffic conditions. The proposed study presents a framework that entails application of the response surface methodology (RSM) to calibrate advanced control system parameters with several contradicting objective functions. RSM was applied to optimize specific control systems with multiple functions for congestion management, actuated split-phasing signal control, transit preemption, and incident detection and management. RSM can effectively handle multiobjective functions by estimating their composite desirability. Parameters considered in this study have been calibrated to simultaneously maximize transit throughput while minimizing travel time. Mathematical models that provide individual measures of effectiveness vis-à-vis various parameters have been developed using RSM under highly and very highly congested situations. Optimum settings, thus obtained, have been validated via simulation testing. The proposed study also examines the robustness of relevant parameter values.