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Fast Model Predictive Control-Based Fuel Efficient Control Strategy for a Group of Connected Vehicles in Urban Road Conditions

机译:基于快速模型预测控制的一组联网车辆在城市道路条件下的节油控制策略

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摘要

In this paper, we develop a fast model predictive control (MPC)-based fuel economic control strategy for a group of connected vehicles in urban road conditions. The proposed control strategy is decentralized in nature, as every vehicle evaluates its own strategy using only neighborhood information. Along with the vehicle-to-vehicle communication, we exploit the signal phase and timing information from traffic lights to develop computationally efficient MPC-based strategies that reduce stopping at red lights and improve the fuel economy for a group of vehicles. The simulation results indicate the improvement in group performance and computational advantages of our proposed method.
机译:在本文中,我们为城市道路条件下的一组联网车辆开发了一种基于快速模型预测控制(MPC)的燃油经济性控制策略。提议的控制策略本质上是分散的,因为每个车辆仅使用邻域信息来评估其自己的策略。与车辆到车辆的通信一起,我们利用交通信号灯的信号相位和定时信息来开发基于计算的高效基于MPC的策略,该策略可减少红灯停车并提高一组车辆的燃油经济性。仿真结果表明,该方法在分组性能和计算优势上均有所提高。

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