Control Strategies for Corridor Management

Details

• Creators:
  Amiri, Zahra ; Lo, Yu-Chieh ; Skabardonis, Alexander ; Varaiya, Pravin
• Corporate Creators:
  University of California, Berkeley. Institute of Transportation Studies
• Subject/TRT Terms:
  • Traffic signal controllers
  • Mathematical models
  • Highway traffic control systems
  • Simulation
  • Traffic simulation
• Publication/ Report Number:
  2016 - TO 008 - 65A0529
• Resource Type:
  Tech Report
• Geographical Coverage:
  North America
• Corporate Publisher:
  California. Dept. of Transportation ; University of California Center on Economic Competitiveness in Transportation
• NTL Classification:
  NTL-SAFETY AND SECURITY-Highway Safety ; NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION ; NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control Devices
• Abstract:
  Integrated management of travel corridors comprising of freeways and adjacent arterial streets can potentially improve the performance of the highway facilities. However, several research gaps exist in data collection and performance measurement, analysis tools and control strategies. In this project first we analyzed high resolution data consisting of time-stamped records of every event involving vehicles, together with the signal phase at real-world signalized intersections and developed procedures for estimating performance measures. Next, we assessed the performance of a new microscopic simulator for signalized arterials. The model predictions were in close agreement with the predictions from widely used models in practice. We also developed and applied control strategies for freeway-arterial coordinated control to avoid queue override and developed a methodology to provide estimates of the amount and impacts of freeway diverted traffic in case of no-recurrent (incident related) congestion.
• Format:
  PDF
• Funding:
  65A0529
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/35494/dot_35494_DS1.pdf
• File Type:
  [PDF - 2.01 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:4652e0c2e830b8977497382c1448aa5859cc88248b63da680ddbc2d849902c34