Network

Cover of Upstream and Downstream Detection to Improve Congested Network Operation
Upstream and Downstream Detection to Improve Congested Network Operation
  • Publication no: AP-R400-12
  • ISBN: 978-1-921991-17-2
  • Published: 28 February 2012

Congestion in Australian cities has continued to get worse with significant increases in population and new car registrations. About a million new motor vehicles per year were registered in Australia in the years 2005-2007 before the global financial crisis (The Motor Report 2008). New vehicle sales has since picked up after the financial crisis and the total number of new registered vehicles was over 1 million in 2010 (Federal Chamber of Automobile Industries 2011). Area traffic control (ATC) systems such as SCATS or STREAMS are critical tools to manage congestion on arterial roads. It is important that the operation of these systems continues to deal effectively with the increasing congestion.

  • 1. INTRODUCTION
  • 2. REVIEW OF RECENT STUDIES
    • 2.1. The Austroads NS1517 Study on Balancing Traffic Density
    • 2.2. Adaptive Area Traffic Control and Detector Locations
      • 2.2.1. Offsets and Spillback
      • 2.2.2. Detector Locations
    • 2.3. The MASCOS Report for VicRoads
    • 2.4. Summary
  • Table 2.2: Comparison of two modelling techniques
  • 3. SETTING UP PRE-EMPTION AND GATING STRATEGIES IN AIMSUN
    • 3.1. Hypothetical Network and Control Strategies
      • 3.1.1. Pre-emption
      • 3.1.2. Gating
    • 3.2. Performance Indicators for Comparative Analysis
    • 3.3. Key AIMSUN Parameters
  • 4. PRE-EMTION SIMULATION RESULTS
    • 4.1. Traffic Demand Profile and Network Congestion
    • 4.2. Pre-emption without Side-street Traffic
      • 4.2.1. Establishing a Base Case with Adaptive Cycle Times
      • 4.2.2. Pre-emption Results and Cycle Time Changes with No Side-street Traffic
    • 4.3. With and Without Pre-emption at 5% and 10% Side-street Traffic
    • 4.4. Detectors at Stopline vs Detectors at the Source
    • 4.5. Summary
  • 5. GATING SIMULATION RESULTS
    • 5.1. Scenarios G1 and G2 – Base Case and Gating
    • 5.2. Scenario G3 – Impact of Cycle Time Decrease on Gating
    • 5.3. Summary
  • 6. CONCLUSIONS AND RECOMMENDATIONS
  • References
  • Appendix A SATURATION FLOWS AND REACTION TIMES IN AIMSUN
  • Appendix B APPLICATION PROGRAMMING INTERFACE (api) FOR AIMSUN SIMULATIONS