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Traffic congestion has long been a worldwide difficult problem in metropolitan transportation networks, incurring tremendous time waste and exhaust pollution. Extensive efforts have been made to address this problem, among which traffic control at intersections is known to be especially crucial while challenging. Also, it is helpful to the recent advent of autopilot technologies by enhancing the schedule accuracy and reducing the infrastructure cost. In practice, however, existing researches can hardly work well in a pervasive manner since they are essentially limited to two ideal assumptions: 1) each intersection comprises four ways; 2) each way is homogeneously composed of two lanes. Through an in-depth examination of their basic models, we find that the two-fold ideal assumptions are largely compelled by the surprisingly high complexity of converting a practical intersection topology into a theoretical conflict graph. Moreover, existing works seldom consider the modeling of complex intersections in the scene of cooperative control of multiply intersections. Driven by the above understandings, our first effort towards a general framework (for handling multiple-way heterogeneous intersections) is to carefully transform a practical intersection topology into a homomorphic, regular conflict graph which is suited to theoretical modeling and further processing with an affordable complexity. Besides, a maximum weight independent set (MWIS) based approach is proposed to minimize the average waiting time of vehicles at an isolated intersection. In addition, we apply a backpressure-based algorithm to our framework to further optimize the global average waiting time of vehicles in a whole road network. Simulation results have demonstrated that the average waiting time achieved by our approach is merely 80 seconds while traditional traffic light control reaches 370 seconds.

A General Framework for Intersection Traffic Control With Backpressure Routing