Modelling supported driving as an optimal control cycle: Framework and model characteristics

Meng Wang, Martin Treiber, Winnie Daamen, Serge P. Hoogendoorn, Bart van Arem

Research output: Contribution to journalArticleResearchpeer-review

23 Citations (Scopus)


Driver 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 characteristics 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.

Original languageEnglish
Pages (from-to)547-563
Number of pages17
JournalTransportation Research Part C: Emerging Technologies
Publication statusPublished - Nov 2013
Externally publishedYes


  • Advanced Driver Assistance Systems
  • Car-following
  • Cooperative systems
  • Optimal control
  • Stability analysis

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