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Multi-objective optimization model for urban traffic intersection control based on Data Fusion

机译:基于数据融合的城市交通交叉控制多目标优化模型

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A new multi-objective optimization control strategy for urban intersection is proposed, which takes the degree of smooth and the degree of equilibrium as objectives. The new method is not limited to the traditional basic traffic parameters, such as delay and queue length.etc, but Applying data fusion technology, by multiple integrating on the basic traffic parameters, the real-time multi-objective values are achieved. The degree of the smooth quantitatively denotes the forced travel time extension because of traffic signal control, saturated traffic flow.ect. The degree of equilibrium denotes the equilibrium degree of traffic flow in space. Illustrating an intersection in Beijing, a simulation model in Paramics is built. The simulation results show that the proposed multi-objective control methods can not only reduce the traffic flow delay, but also makes traffic flow distributing equilibrium in each phase of intersection. This approach is consistent with Chinese saturated traffic flow characteristics.
机译:提出了一种新的多目标优化控制策略,为城市交叉路口提供了平稳程度和均衡程度作为目标。新方法不限于传统的基本流量参数,如延迟和队列长度.ETC,但应用数据融合技术,通过对基本流量参数的多个集成,实现实时多目标值。流畅的程度,定量表示由于交通信号控制,饱和的流量流量而被强制旅行时间延伸。平衡程度表示空间中交通流量的平衡度。说明北京的交叉点,建立了Paramics的仿真模型。仿真结果表明,所提出的多目标控制方法不仅可以降低交通流量延迟,还可以在交叉口的每个阶段进行交通流量分配平衡。这种方法与中国饱和的交通流特征一致。

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