Adaptive Traffic Light Control of Multiple Intersections in WSN-Based ITS

We investigate the problem of adaptive traffic light control of multiple intersections using real-time traffic data collected by a wireless sensor network (WSN). Previous studies mainly focused on optimizing the intervals of green lights in fixed sequences of traffic lights and ignored the traffic flow's characteristics and special traffic circumstances. In this paper, we propose an adaptive traffic light control scheme that adjusts the sequences of green lights in multiple intersections based on the real- time traffic data, including traffic volume, waiting time, number of stops, and vehicle density. Subsequently, the optimal green light length can be calculated from the local traffic data and traffic condition of neighbor intersections. Simulation results demonstrate that our scheme produces much higher throughput, lower average waiting time and fewer number of stops, compared with three control approaches: the optimal fixed-time control, an actuated control and an adaptive control.