Optimal signal timing design for urban street networks under user equilibrium based traffic conditions : final report.

Details

• Creators:
  Li, Zongzhi ; Du, Lili ; Liu, Yi
• Corporate Creators:
  Illinois Institute of Technology
• Corporate Contributors:
  NEXTRANS Center (U.S.) ; United States. Department of Transportation. Research and Innovative Technology Administration ; United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Heuristic methods
  • Optimization
  • Traffic assignment
  • Traffic congestion
  • Traffic delays
  • Traffic flow
  • Traffic signal timing
  • Urban areas Bilevel optimization
  • user equilibrium
• Publication/ Report Number:
  NEXTRANS Project No. 019FY02
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Illinois;Chicago (Illinois)
• Edition:
  Final report
• Corporate Publisher:
  Purdue University
• Abstract:
  In the ever-growing travel demand, traffic congestion on freeways and expressways ; recurs more frequently at a higher number of locations and for longer durations with ; added severity. This becomes especially true in large metropolitan areas. Particular to the ; urban areas, excessive crowdedness caused by inefficient traffic control also results in ; urban street networks operating in near or over-saturated conditions, leading to unpleasant ; travel experience due to long delays at intersections. As a consequence, the recurrent ; traffic congestion on roadway segments and vehicle delays at intersections inevitably ; compromise energy efficiency, traffic mobility improvement, safety enhancement, and ; environmental impacts mitigation. All too often, neither restraining travel demand nor ; expanding system capacity is desirable and practical. Conversely, effectively utilizing the ; capacity of the existing transportation system has been increasingly thought of as the ; solution to congestion relief. With respect to the urban street networks, developing ; effective means for urban intersection signal optimization becomes essential to reduce ; intersection delays. ; Conventional signal timing optimization methods use historical traffic data and ; assume that traffic flows will remains unchanged after the implementation of new signal ; timing plans. Traffic flows are assumed to be constant, but in fact, when signal timing ; plans change, travel times for some travel routes will alter, which requires drivers in the ; network to adjust their choice of travel routes to arrive at the destinations, and result in redistribution of traffic in the network. Therefore, the effects of interactions between ; signal timing plans and traffic flows need to be explicitly taken into consideration. This ; study introduces a new methodology that jointly considers signal timing optimization and ; traffic assignment in an overall analytical framework that contains model formulations ; under assumptions consistent with real world situations. Such a framework is well suited ; for applications in real world cases. Specifically, the overall optimization framework is ; formulated as a bi-level optimization problem. In the proposed basic model, at the upper ; level, a traffic signal timing optimization problem for urban network is introduced to ; minimize system total travel time by optimizing signal green splits. At the lower level, a ; static user equilibrium problem is formulated for networkwide traffic assignment. In the ; vehicle delay estimation, the time-dependent stochastic delay model in the 2010 Highway ; Capacity Manual (HCM 2010) is employed and formulated as Variational Inequality ; constraints, what allow the state-of-the-art MPEC solver, GAMS/NLPEC, to solve the ; problem for a local optimal effectively and efficiently. The bi-level optimization model is ; first tested using a small network (the test network) and a computational experiment using ; a subarea network in the Chicago central district is conducted to assess the practicality of ; the model formulation in real world applications. In order to import more reality to the basic model and also consider the potential ; system benefit that comes from different signal phasing design, an enhanced model is ; developed based on the basic model by employing integer and binary variables. ; Formulating the problem with binary variables allows for the selection of proper phasing ; design. Heuristic solution methods are proposed and tested using the test network.
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• Format:
  PDF
• Funding:
  DTRT12-G-UTC05
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/31471/dot_31471_DS1.pdf
• File Type:
  [PDF - 809.87 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:8a389541a37708a7d33cbe228dd31d5c9a755c7490ac1d14b799f6f09cf40618add53be4256d81f5fd097bc05ccdb698944712f56c56afeaec0711f61c3fd293