The traffic congestion phenomenon in bottleneck areas is always a difficult problem that occurs in many freeways. To reduce traffic congestion and improve the safety of bottleneck areas, a dynamic speed control method is proposed using connected and au-tonomous vehicle (CAV) technology. First, the traditional cell transmission model (CTM) is improved to describe the capacity drop phenomenon at the freeway bottleneck in mixed CAV and human-driven vehicle (HV) traffic flow. Then, a model predictive control (MPC)-based variable speed control (MVSC) is proposed to limit the dynamic speed of CAVs in multiple minor sections separately considering the dynamic transmission of the congestion area. Subsequently, a particle swarm optimization (PSO) algorithm is adopted to solve the control model. Finally, the proposed multiple-sections MVSC and two other methods, the no variable speed control (NVSC) and the feedback variable speed control (FVSC), are analysed and compared. The results showed that the MVSC strategy proposed in this paper could effectively improve traffic efficiency and safety compared to NVSC and FVSC, even in a low CAV penetration rate environment.(c) 2023 Elsevier B.V. All rights reserved.
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KTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, SwedenKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Cicic, Mladen
Xiong, Xi
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NYU Tandon Sch Engn, Dept Civil & Urban Engn, C2SMART Univ Transportat Ctr, Brooklyn, NY 11201 USAKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Xiong, Xi
Jin, Li
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Univ Michigan Shanghai Jiao Tong Univ Joint Inst, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
NYU Tandon Sch Engn, Brooklyn, NY 11201 USAKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Jin, Li
Johansson, Karl Henrik
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KTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, SwedenKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
机构:
KTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, SwedenKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Cicic, Mladen
Xiong, Xi
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机构:
NYU Tandon Sch Engn, Dept Civil & Urban Engn, C2SMART Univ Transportat Ctr, Brooklyn, NY 11201 USAKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Xiong, Xi
Jin, Li
论文数: 0引用数: 0
h-index: 0
机构:
Univ Michigan Shanghai Jiao Tong Univ Joint Inst, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
NYU Tandon Sch Engn, Brooklyn, NY 11201 USAKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden
Jin, Li
Johansson, Karl Henrik
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h-index: 0
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KTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, SwedenKTH Royal Inst Technol, Div Decis & Control Syst, S-10044 Stockholm, Sweden