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Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

机译:基于无线传感器网络的交通拥堵评估和信号控制优化:型号和算法

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摘要

This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.
机译:本文介绍了基于无线传感器网络的交通流量数据监控和最优流量光控制的模型和算法。鉴于传感器节点沿着信号交叉路口之间的段稀疏地部署的场景,使用连续uM流量方程构建分析模型,并开发估算散射传感器数据的流量参数的方法。基于交通数据和交通拥堵形成的原理,我们介绍了可用于评估段沿着段的实时交通拥塞状态的拥塞因素,并预测交通堵塞的子临界状态。结果预计将支持交通灯控制的时序阶段优化,以避免在其形成之前避免交通拥堵。我们基于移动世纪数据集模拟交通监控,并在信号定时优化模型中分析vissim平台上的交通灯控制性能。仿真结果表明,该方法可以提高交通数据监控的空间时间分辨率,并以高精度评估交通拥堵状态。有助于显着减轻城市交通拥堵,并降低平均交通延误和最大队列长度。

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