Optimal signal timing design for urban street networks under user equilibrium based traffic conditions : final report.
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2016-09-20
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Edition:Final report
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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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