Emission Mitigation via Longitudinal Control of Intelligent Vehicles in a Congested Platoon
Emission Mitigation via Longitudinal Control of Intelligent Vehicles in a Congested Platoon
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DOI：
10.1111/mice.12130
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发表时间：
2015-06
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影响因子：
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通讯作者：
Zhaodong Wang;X. Chen;Y. Ouyang;Meng Li
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文献类型：
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作者：
Zhaodong Wang;X. Chen;Y. Ouyang;Meng Li
驾驶员的汽车跟随行为，加上对环境状况的不准确感知，导致了拥堵的高速公路交通中的振荡和大量排放。智能车辆和现代通信技术的出现为减少人为因素的不利影响和动态控制尾随车辆提供了机会。本文提出了一种非线性模型预测控制（MPC）方法，通过纵向控制拥挤队列中的智能车辆来减少排放。为了减轻实时优化的负担，我们还提出了一种瞬时控制模型，它本质上是一种简化的MPC方法，具有短而相同的预测和控制范围。通过一系列仿真对所提出的车辆控制策略进行了测试，结果验证了少量智能车辆的局部和瞬时控制可以减少一排车辆的排放。将该模型应用于现场轨迹数据，结果表明瞬时排放优化模型在不增加行程时间的情况下显著降低了排放。研究发现，随着智能车辆在拥堵车辆排中的比例（渗透率）的增加，所提出的车辆控制在减少排放和稳定交通方面的有效性也会增加。
Drivers' car‐following behavior, coupled with inaccurate perception of ambient conditions, contributes to oscillations and significant emissions in congested highway traffic. The emergence of intelligent vehicles and modern communication technologies provides an opportunity to reduce adverse impacts of human factors and dynamically control car‐following vehicles. This article proposes a nonlinear model predictive control (MPC) approach for emission mitigation via longitudinal control of intelligent vehicles in a congested platoon. To relieve the real‐time optimization burden, we also propose an instantaneous control model which is essentially a simplified MPC approach with a short and identical prediction and control horizon. The proposed vehicle control strategies are tested using a series of simulations, and results verify that localized and instantaneous control of a few intelligent vehicles could reduce emissions of a platoon of vehicles. The proposed models are also applied to field trajectory data, and results show that the instantaneous emission optimization model significantly reduces emissions without increasing travel time. The effectiveness of the proposed vehicle control on emission mitigation and traffic stabilization is found to increase with the percentage (penetration rate) of intelligent vehicles in the congested vehicle platoon.