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  • 标题:Modelling Supported Driving as an Optimal Control Cycle: Framework and Model Characteristics
  • 本地全文:下载
  • 作者:Meng Wang ; Meng Wang ; Martin Treiber
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2013
  • 卷号:80
  • 页码:491-511
  • DOI:10.1016/j.sbspro.2013.05.027
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractDriver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of automated vehicles are controlled to optimise a cost function, assuming other vehicles driving at stationary conditions over a prediction horizon. The flexibility of the framework is demonstrated with controller design of Adaptive Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and C-ACC model characteristics are investigated analytically, with focus on equilibrium solutions and stability properties. The proposed ACC model produces plausible human car-following behaviour and is unconditionally locally stable. By careful tuning of parameters, the ACC model generates similar stability charac- teristics as human driver models. The proposed C-ACC model results in convective downstream and absolute string instability, but not convective upstream string instability observed in human-driven traffic and in the ACC model. The control framework and analytical results provide insights into the influences of ACC and C-ACC systems on traffic flow operations.
  • 关键词:Advanced Driver Assistance Systems;Cooperative Systems;car-following;optimal control;stability analyses
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