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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Big data oriented intelligent traffic evacuation path fuzzy control system
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Big data oriented intelligent traffic evacuation path fuzzy control system

机译:大数据导向智能交通疏散路径模糊控制系统

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摘要

The current traffic evacuation path control system has high risk coefficient and path congestion, and low efficiency and system error coefficient. For this problem, a fuzzy control system of traffic evacuation path based on genetic method is proposed and designed in this paper. The data server, geographic information server, computing server, and application server are used to construct the system framework. The logical structure is divided into data source layer, data access layer, scheduling layer, computing model layer, and application interface layer. The function module is mainly composed of static data management module, emergency management module, dynamic data interface module, dynamic traffic assignment module, guidance information release module, and user management module. The system hardware is designed by using the logical structure in combination with the function module. In the system software, the coordinator-operator mode is introduced into the real-time computing operation mechanism. The interaction of the coordinator and the operator is to implement the user specified operational function. Traffic data is forecast by autoregressive model. It is substituted into the objective function of intelligent traffic evacuation and the genetic method is used to solve the objective function. At last, fuzzy control result of optimal traffic evacuation path is obtained. Experimental results show that the average risk coefficient in the evacuation process is about 0.27, the average time consuming is 0.3 h, and the congestion of the evacuation path is relatively low, so the fault tolerance coefficient of the system can be controlled within a reasonable range. The system has a good overall operation effect and is feasible.
机译:目前的流量疏散路径控制系统具有高风险系数和路径拥塞,效率低,系统误差系数。对于这个问题,提出了一种基于遗传方法的交通疏散路径模糊控制系统,并设计了本文。数据服务器,地理信息服务器,计算服务器和应用程序服务器用于构建系统框架。逻辑结构分为数据源层,数据访问层,调度层,计算模型层和应用程序界面层。该功能模块主要由静态数据管理模块,紧急管理模块,动态数据接口模块,动态流量分配模块,指导信息释放模块和用户管理模块组成。系统硬件是通过使用与功能模块组合使用的逻辑结构来设计的。在系统软件中,协调器操作模式被引入实时计算操作机制。协调器和操作员的交互是实现用户指定的操作功能。自回归模型预测交通数据。它被取代为智能交通疏散的目标函数,并使用遗传方法来解决客观函数。最后,获得了最佳流量抽空路径的模糊控制结果。实验结果表明,抽空过程中的平均风险系数约为0.27,平均耗时为0.3小时,抽空路径的拥塞相对较低,因此系统的容错系数可以在合理的范围内控制。该系统具有良好的整体运行效果,是可行的。

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