Dynamic Traffic Control with Fairness and Throughput Optimization Using Vehicular Communications

Traffic congestion in modern cities seriously affects our living quality and environments. Inefficient traffic management leads to fuel wastage in volume of billion gallons per year. In this paper, we propose a dynamic traffic control framework using vehicular communications and fine-grained information, such as turning intentions and lane positions of vehicles, to maximize traffic flows and provide fairness among traffic flows. With vehicular communications, the traffic controller at an intersection can collect all fine-grained information before vehicles pass the intersection. Our proposed signal scheduling algorithm considers the flows at all lanes, allocates more durations of green signs to those flows with higher passing rates, and also gives turns to those with lower passing rates for fairness provision. Simulation results show that the proposed framework outperforms existing works by significantly increasing the number of vehicles passing an intersection while keeping average waiting time low for vehicles on non-arterial roads. In addition, we discuss our implementation of an Zigbee-based prototype and experiences.