• DocumentCode
    2347772
  • Title

    Empirical Slow-to-Start Behavior from NGSIM Trajectory Data

  • Author

    Li, Xingang ; Jia, Bin ; Gao, Ziyou

  • Author_Institution
    MOE Key Lab. for Urban Transp. Complex Syst. Theor. & Technol., Beijing Jiaotong Univ., Beijing, China
  • fYear
    2011
  • fDate
    15-19 April 2011
  • Firstpage
    1069
  • Lastpage
    1073
  • Abstract
    The slow-to-start rule is usually adopted in cellular automaton traffic flow model. And it is deemed as the mechanism for metastable states and hysteresis effect. In this paper, we explore the slow-to-start behavior by analyzing the vehicle trajectory data provided by the Next Generation Simulation program. Then the slow-to-start rule is verified in several cellular automaton traffic flow models. The results show that the acceleration rate will increases as the speed increasing. The starting up gap does not change while the acceleration rate increases as the stop time becomes larger. The slow-to start behavior really exist, and the slow-to-start rule in VDR model is realistic. But the slow-to-start rule in MCD model is not consistent with empirical results.
  • Keywords
    cellular automata; road traffic; MCD model; NGSIM trajectory data; VDR model; cellular automaton traffic flow model; empirical slow-to-start behavior; hysteresis effect; metastable states; next generation simulation program; vehicle trajectory data; Acceleration; Data models; Mathematical model; Smoothing methods; Trajectory; Vehicles; Slow-to-start rule; cellular automaton; traffic flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
  • Conference_Location
    Yunnan
  • Print_ISBN
    978-1-4244-9712-6
  • Electronic_ISBN
    978-0-7695-4335-2
  • Type

    conf

  • DOI
    10.1109/CSO.2011.127
  • Filename
    5957840