Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies
Mahyar Amirgholy and
H. Oliver Gao
Transportation Research Part B: Methodological, 2017, vol. 104, issue C, 215-237
Abstract:
The macroscopic fundamental diagram (MFD) is introduced in recent studies to present the relationship between the flow and the density of the network in large urban regions (neighborhoods). The MFD can be also rescaled to approximate network outflow as a function of the vehicular accumulation of the system in the morning commute problem. In this research, we develop a bathtub model (macro-scale traffic congestion model) by combining Vickrey's (1969) model of dynamic congestion with the MFD to formulate the user equilibrium over the peak as an ordinary differential equation (ODE). This problem can be solved numerically to estimate the exact solution of the morning commute problem. Alternatively, the morning commute problem can be solved analytically by approximating the solution of the ODE using a well-behaved function. Here, we present a quadratic and also a linear approximation of the equilibrium solution for a semi-quadratic MFD, considering that the declining part of the MFD is shown to be well estimated by a quadratic function. To optimize the system, we present pricing strategies for network users (dynamic tolling) and employers inside the region (dynamic taxing) that can minimize the generalized cost of the system by keeping the outflow maximized over the peak. Finally, we compare the exact and the approximate solutions of the problem, and also the proposed pricing strategies of the region in a numerical example.
Keywords: Bathtub model; Macroscopic fundamental diagram; Analytical solution; Dynamic tolling and taxing; Staggerd working hours (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (17)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:transb:v:104:y:2017:i:c:p:215-237
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DOI: 10.1016/j.trb.2017.07.006
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