A Decentralized Model Predictive Control Strategy for Heterogeneous Vehicle Platoon Pertaining of Connected Automated Vehicles and Human Driven Vehicles
编号:82 访问权限:仅限参会人 更新:2021-12-03 10:13:32 浏览:144次 张贴报告

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摘要
Full connected and automated vehicle (CAV) market penetration rate can be highly unrealistic in the near future which leads to a transition period of mixed traffic environment. Thereby, this paper proposes a decentralized model predictive control (DMPC) strategy for heterogeneous vehicle platoon pertaining of CAVs and human driven vehicles (HV) under a dynamic two-predecessor-following information topology (DTIT) considering communication failure. The illustrious intelligent driver model (IDM) is applied to model and predict HV’s driving behavior. Three various scenarios of platoon composition are developed depending on the different percentage and positions of HVs. The objective cost function is designed by penalizing on the deviations between the actual and desired trajectories and constraints are proposed to help stabilize the whole platoon system and attenuate oscillation more effectively. The application of DTIT depicts the flexibility of system communication and the effectiveness of control degradation avoidance. Several field test based numerical simulated experiments demonstrate the developed DMPC outperforms than the normal cooperative adaptive cruise control (CACC) strategy without prediction.
关键词
CICTP
报告人
Jiwan Jiang
southeast university

稿件作者
Jiwan Jiang southeast university
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重要日期
  • 会议日期

    12月17日

    2021

    12月20日

    2021

  • 12月16日 2021

    报告提交截止日期

  • 12月24日 2021

    注册截止日期

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Chinese Overseas Transportation Association
Chang'an University
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