A supervised switching-mode observer of traffic state and parameters and application to adaptive ramp metering

Yue Zhou, Kaan Ozbay, Pushkin Kachroo, Edward Chung

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Traffic state observers derived from the cell transmission model (CTM) are vulnerable to incorrect information and time variation of traffic flow parameters, in particular the critical density, known as the issue of mismodelling, which can cause erroneous mode switching of CTM-based observers to undermine estimation and control. This issue cannot be completely overcome, even if traffic flow parameters are augmented into state vector. We propose coupling a supervisor to the standard CTM-EKF observer to completely resolve this issue. Simulation shows that the proposed supervised observer can switch modes in accordance with actual situations and generate quality estimates of both traffic state and parameters. The supervised observer is then integrated with ramp metering control. Simulation shows that, in an environment of time-varying traffic flow parameters, the supervised observer-based ramp metering control system considerably outperforms an ordinary observer-based ramp metering control system, which only updates traffic state in real time.

Original languageEnglish
JournalTransportmetrica A: Transport Science
Publication statusAccepted/In press - 2021


  • cell transmission model
  • extended Kalman filter
  • parameter estimation
  • ramp metering
  • Traffic state estimation

ASJC Scopus subject areas

  • Transportation
  • Engineering(all)

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