An Improved Adaptive Signal Control Method for Isolated Signalized Intersection Based on Dynamic Programming

The performance of an adaptive signal control system largely depends on the embedded traffic flow prediction and control algorithm. This paper proposes an improved adaptive control method, comprised of a vehicle arrival estimation model and a signal optimization algorithm. Firstly, a microscopic model was developed to capture vehicle arrival dynamics both in red and green durations. Based on the upstream detection information, vehicle arrival time is predicted taking account of signal timing, vehicle trajectory and variable queue length. The real-time signal control algorithm was formulated based on a Dynamic Programming (DP) procedure, supporting NEMA phase configuration. Three objective functions were considered respectively, namely minimization of delay, queue length and maximization of throughput. The proposed adaptive control method was implemented in VISSIM on a real signalized intersection. It is shown that DP with NEMA generally outperforms DP with 4-phase and the signal timings generated by SYNCHRO. Different objective functions lead to different control performance in terms of various demands and planning horizons. It is reasonably believed that the model has potential applicability in real time traffic adaptive signal control systems.