ACP based self-learning control for urban intersection

Abstract

The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.