A robust signal control system for equilibrium flow under uncertain travel demand and traffic delay

A robust signal control system (AROSS) for equilibrium flow is presented for urban road networks under uncertain travel demand and traffic delay. The optimal solutions for AROSS can be formulated as a smoothing mathematical program with equilibrium constraints (SMPEC) and efficiently solved by a projected bundle set method with global convergence. While conventional robust optimization is considered a good alternative against high-consequence realization of uncertainty, a traffic responsive signal control using a hybrid strategy of scenarios is considered. Sensitivity analysis of SMPEC with respect to signal settings against randomized budget uncertainty in travel demand and link delay is performed. Numerical comparisons are also made with other heuristics using real-data road networks. Results indicate that AROSS enjoyed a greater gain of achieving road network robustness while effectively attenuating sub-optimality of robust optimum as compared to recent alternatives.