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.
  
  
• Format:
  PDF
• Funding:
  DTRT12-G-UTC05
• Collection(s):
  University Transportation Centers US Transportation Collection
• Main Document Checksum:
  urn:sha-512:8a389541a37708a7d33cbe228dd31d5c9a755c7490ac1d14b799f6f09cf40618add53be4256d81f5fd097bc05ccdb698944712f56c56afeaec0711f61c3fd293
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/31471/dot_31471_DS1.pdf
• File Type:
  [PDF - 809.87 KB ]