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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System
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Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

机译:大型系统在高速公路智能空间中多组车辆的分布式模型预测控制

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摘要

The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS) and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.
机译:提出了基于分布式模型预测控制方法的三类预警距离,用于解决大型多组车辆安全驾驶特性对公路隧道环境的影响。一般来说,系统包括两个部分。首先,将多个车辆分为多个组。同时,提出了一种分布式模型预测控制方法来计算各组的信息框架。每组优化性能都考虑局部优化和优化特征的相邻子组,这可以确保全局优化性能。其次,基于高速公路智能空间(HIS)的基本原理,研究了三种时间预警距离,并针对多组车辆提出了信息框架的概念。建立数学模型可避免车辆避开链条。结果表明,所提出的高速公路智能空间方法能够有效地保证在雾,雨,雪环境下多组车辆的行驶安全性。

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