Abstract

In order to improve the traffic efficiency of official vehicles in the traffic road network, a backpressure routing control strategy for multi-commodity flow (official traffic flow) using official vehicle network environmental data information is proposed. Firstly, the road network composed of official service vehicle-mounted wireless network nodes is used to collect information on road conditions and official service vehicles. In order to improve the real-time and forward-looking route control, an official service vehicle flow forecasting method is introduced to construct a virtual official service vehicle queue. A multi-commodity flow (official service vehicle flow) backpressure route method is proposed, and an official service vehicle control strategy is designed to improve the self-adaptive route of K-means algorithm. In addition, the weight of backpressure strategy is improved according to traffic pressure conditions, and the adaptability of backpressure route algorithm is improved by using optimized parameters. Finally, the simulation results show that the proposed method can effectively control traffic vehicles and improve traffic smoothness.

中文翻译：

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改进的K-means算法在公务车联网环境中的应用与研究

摘要

为了提高交通路网中公务车的通行效率，提出了利用公务车网环境数据信息进行多商品流（公务流）的反压路径控制策略。首先，由公务车载无线网络节点组成的道路网络用于收集路况和公务车辆的信息。为了改善实时性和前瞻性的路线控制，引入了公务车流量预测方法来构建虚拟公务车队列。提出了一种多商品流（公务车流）反压路线方法，设计了一种公务车控制策略，以改进K均值算法的自适应路线。此外，根据交通压力条件提高了反压策略的权重，并通过优化参数提高了反压路径算法的适应性。仿真结果表明，该方法能够有效地控制交通车辆，提高交通通畅性。