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Cooperative Adaptive Cruise Control and exhaust emission evaluation under heterogeneous connected vehicle network environment in urban city

机译:异构互联车辆网络环境下的城市自适应自适应巡航控制与尾气排放评估

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摘要

With the development of information communication and artificial intelligence, the ICV (intelligent connected vehicle) will inevitably play an important part in future urban transport system. In this paper, we study the car following behaviour under the heterogeneous ICV environment. The time to receive information varies from vehicle to vehicle, since the manual vehicles and autonomous vehicles co-exist on the road. By introducing time-varying lags function, a new car following model is proposed, and the cooperative control strategy of this model is studied. Based on Lyapunov function theory and linear matrix inequality (LMI) approach, the sufficient condition that the existence of the feedback controller is given, which makes the closed-loop system asymptotically stable under mixed traffic flow environment. That is to say, traffic congestion phenomenon under heterogeneous traffic flow can be effectively suppressed, and the feedback controller gain matrix can be obtained via solving linear matrix inequality. Finally, by simulation the method is verified effective in alleviating traffic congestions and reducing fuel consumption and exhaust emissions. It could be a useful reference to Cooperative Vehicle Infrastructure System and Smart City.
机译:随着信息通信和人工智能的发展,ICV(智能互联汽车)将不可避免地在未来的城市交通系统中发挥重要作用。在本文中,我们研究了在异构ICV环境下的汽车跟随行为。信息的接收时间因车辆而异,因为手动和自动驾驶车辆在道路上共存。通过引入时变滞后函数,提出了一种新的汽车跟随模型,并研究了该模型的协调控制策略。基于Lyapunov函数理论和线性矩阵不等式(LMI)方法,给出了存在反馈控制器的充分条件,使得混合交通流环境下的闭环系统渐近稳定。也就是说,可以有效地抑制异构流量下的流量拥塞现象,通过求解线性矩阵不等式可以得到反馈控制器增益矩阵。最后,通过仿真验证了该方法在缓解交通拥堵,减少油耗和尾气排放方面的有效性。它可能对合作车辆基础设施系统和智慧城市有用。

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