Application of dynamic traffic assignment to advanced managed lane modeling.

Details

• Creators:
  Hadi, Mohammed ; Shabanian, Shaghayegh ; Ozen, Halit ; Xiao, Yan ; Doherty, Michael ; Segovia, Cesar ; Ham, Heejoo
• Corporate Creators:
  Florida International University. Lehman Center for Transportation Research ; URS Consultants ; Citilabs
• Subject/TRT Terms:
  • Managed lanes
  • Traffic models
  • Dynamic traffic assignment
  • Congestion management systems
  • Congestion pricing
  • Travel demand
  • Simulation
• Publication/ Report Number:
  BDK80-977-30
• Resource Type:
  Tech Report
• Geographical Coverage:
  Florida
• Corporate Publisher:
  Florida. Department of Transportation. Office of Research Development
• Abstract:
  In this study, a demand estimation framework is developed for assessing the managed lane (ML) ; strategies by utilizing dynamic traffic assignment (DTA) modeling, instead of the traditional ; approaches that are based on the static traffic assignment (STA). The framework includes ; methods for calibrating the network (supply), demand, and assignment modeling parameters. ; The methods were extensively tested using real-world data to assure that the DTA modeling of ; managed lanes reflected real-world conditions and responded reasonably to different congestion ; management scenarios, such as variable pricing policies and different levels of willingness to ; pay. This framework is standalone and independent of the utilized DTA modeling tool.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/26857/dot_26857_DS1.pdf
• File Type:
  [PDF - 7.62 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:82f4bf586c74a6f5a05bb51da6e8112c2190b98cfc6bf2d041403112c50a8756692cbabf8ff37ec044edf5e884409f3486cc0f531961ea1ca293a1a4bda9e480