We investigate the problem of adaptive traffic light control of multiple intersections using real... more 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.
We investigate the problem of adaptive traffic light control using real-time traffic information ... more We investigate the problem of adaptive traffic light control using real-time traffic information collected by a wireless sensor network (WSN). Existing studies mainly focused on determining the green light length in a fixed sequence of traffic lights. In this paper, we propose an adaptive traffic light control algorithm that adjusts both the sequence and length of traffic lights in accordance with the real time traffic detected. Our algorithm considers a number of traffic factors such as traffic volume, waiting time, vehicle density, etc., to determine green light sequence and the optimal green light length. Simulation results demonstrate that our algorithm produces much higher throughput and lower vehicle's average waiting time, compared with a fixed-time control algorithm and an actuated control algorithm. We also implement proposed algorithm on our transportation testbed, iSensNet, and the result shows that our algorithm is effective and practical.
We investigate the problem of adaptive traffic light control of multiple intersections using real... more 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.
We investigate the problem of adaptive traffic light control of multiple intersections using real... more 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.
We investigate the problem of adaptive traffic light control using real-time traffic information ... more We investigate the problem of adaptive traffic light control using real-time traffic information collected by a wireless sensor network (WSN). Existing studies mainly focused on determining the green light length in a fixed sequence of traffic lights. In this paper, we propose an adaptive traffic light control algorithm that adjusts both the sequence and length of traffic lights in accordance with the real time traffic detected. Our algorithm considers a number of traffic factors such as traffic volume, waiting time, vehicle density, etc., to determine green light sequence and the optimal green light length. Simulation results demonstrate that our algorithm produces much higher throughput and lower vehicle's average waiting time, compared with a fixed-time control algorithm and an actuated control algorithm. We also implement proposed algorithm on our transportation testbed, iSensNet, and the result shows that our algorithm is effective and practical.
We investigate the problem of adaptive traffic light control of multiple intersections using real... more 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.
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Papers by BINBIN ZHOU