Q-learning and Approximate Dynamic Programming for Traffic Control: A Case Study for an Oversaturated Network

Results from a realistic test network shows that the two methods used to control the traffic signals in an oversaturated network are suitable for controlling the signals in oversaturated conditions by preventing long-lasting queue spillovers and gridlocks.