Arrival rate identification for a class of traffic signal control problem

Setting signals at traffic intersections to reduce congestion is one of the most challenging problems in traffic management. To find the optimal control strategy, specific information of the traffic flows passing through intersections must be provided in advance. It has been shown that the Markovian decision control theory can be successfully applied to solve traffic signal control problems, when both the state transition probabilities and the one-step reward function are known. In this paper, an online parameter identification algorithm is investigated for adaptive Markovian decision control at an isolated traffic intersection with unknown vehicle arrival rates. The authors give a brief introduction to Markovian control processes and a maximum likelihood estimation algorithm, and discuss the traffic dynamic equations and the adaptive Markovian decision control model for an isolated traffic intersection.. The proposed algorithm is then tested by computer simulation and the result is shown.