Optimization of Control Parameters for Adaptive Traffic- Actuated Signal Control

This paper proposes a real-time adaptive control model for signalized intersections that decides optimal control parameters commonly found in modern actuated controllers, aiming to exploit the adaptive functionality of traffic-actuated control and to improve the performance of traffic-actuated signal system. This model incorporates a flow prediction process that estimates the future arrival rates and turning proportions at target intersection based on the available detector information and signal timing plan. Signal control parameters are optimized dynamically cycle-by-cycle to satisfy these estimated demands. The proposed adaptive control strategy is tested on a network consisting of thirty-eight actuated signals using microscopic simulation. Simulation results show the proposed adaptive model is able to improve the performance of the study network, especially under off-peak traffic conditions