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Model Predictive Control for Intelligent Speed Adaptation in Intelligent Vehicle Highway Systems

机译:智能车辆公路系统智能速度适应模型预测控制

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Intelligent Vehicle Highway Systems (IVHS) consist of automated highway systems in combination with intelligent vehicles and roadside controllers. The intelligent vehicles can communicate with each other and with the roadside infrastructure. The vehicles are organized in platoons with short intraplatoon distances, and larger distances between platoons. Moreover, all vehicles are assumed to be automated, i.e., throttle, braking, and steering commands are determined by an automated on-board controller. In this paper we first propose a model predictive control (MPC) approach to determine appropriate speeds for the platoons. Next, we discuss which prediction models are suited to be used as an on-line traffic prediction model in MPC for IVHS. The proposed approach is then applied to a simple simulation example in which the aim is to minimize the total time all vehicles spend in the network by optimally assigning speeds to the platoons.
机译:智能车辆公路系统(IVHS)由自动化高速公路系统组成,与智能车辆和路边控制器组合。智能车辆可以彼此沟通和路边基础设施。车辆在具有短的跨界距离距离的粘盘中组织,塔板之间的距离更大。此外,假设所有车辆都是自动化的,即节流,制动和转向命令由自动车载控制器确定。在本文中,我们首先提出了一种模型预测控制(MPC)方法来确定压胶的适当速度。接下来,我们讨论哪种预测模型适合用作IVHS的MPC中的在线交通预测模型。然后将所提出的方法应用于一个简单的模拟示例,其中目的是通过最佳地将速度分配给粘盘来最小化网络中所有车辆的总时间。

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