Optimizing Network Flows with Congestion-Based Flow Reductions

When optimizing traffic systems using time-expanded network flow models, traffic congestion is an important consideration because it can decrease both the discharge traffic flow rate and speed. One widely used modeling framework is the Cell Transmission Model (CTM) (see Daganzo, Transp Res-B 28(4):2...

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Published in:Networks and spatial economics Vol. 13; no. 3; pp. 283 - 306
Main Authors: Bish, Douglas R., Chamberlayne, Edward P., Rakha, Hesham A.
Format: Journal Article
Language:English
Published: Boston Springer US 01.09.2013
Springer Nature B.V
Subjects:
Civil Engineering
Congestion
Discharge
Economic models
Economic statistics
Economic theory
Economics
Economics and Finance
Evacuation
Linear programming
Network flow problem
Networks
Operations Research/Decision Theory
Optimization
Propagation
Reduction
Regional/Spatial Science
Studies
Traffic assignment
Traffic congestion
Traffic control
Traffic engineering
Traffic flow
Mixed binary programming
Cell Transmission Model (CTM)
Congestion
Time-expanded network flows
Evacuation planning/modeling
ISSN:1566-113X, 1572-9427
Online Access:Get full text
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Summary:When optimizing traffic systems using time-expanded network flow models, traffic congestion is an important consideration because it can decrease both the discharge traffic flow rate and speed. One widely used modeling framework is the Cell Transmission Model (CTM) (see Daganzo, Transp Res-B 28(4):269–287, 1994 , Transp Res-B 29(2):79–93, 1995 ), which is implemented in a linear program (LP) in Ziliaskopoulos (Transp Sci 34(1):37–49, 2000 ). While the CTM models the reduction in speed associated with congestion and the backward propagation of congestion, it does not properly model the reduction in discharge flow from a bottleneck after the onset of congestion. This paper discusses this issue and proposes a generalization of the CTM that takes into account this important phenomena. Plainly, an optimization that does not consider this important negative result of congestion can be problematic, e.g., in an evacuation setting such an optimization would assume that congestion does not impact network clearance time, which can result in poor evacuation strategies. In generalizing the CTM, a fairly simple modification is made, yet it can have significant impacts on the results. For instance, we show that for the generalized CTM the traffic holding (a result of the linearization of the CTM flow constraints) plays a more harmful role, which thus requires a scheme to eliminate traffic holding. In this paper, we propose a mixed binary program to eliminate traffic holding, along with methods to improve solvability.
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ISSN:1566-113X
1572-9427
DOI:10.1007/s11067-012-9181-3