Agent-Based Simulation Model for Assessment of Financing Scenarios in Highway Transportation Infrastructure Systems
Authored by Amr Kandil, Ali Mostafavi, Dulcy Abraham, Daniel DeLaurentis, Joseph Sinfield, Cesar Queiroz
Date Published: 2016
DOI: 10.1061/(asce)cp.1943-5487.0000482
Sponsors:
No sponsors listed
Platforms:
No platforms listed
Model Documentation:
UML
Other Narrative
Flow charts
Model Code URLs:
Model code not found
Abstract
There is an urgent need for policies to close the existing financing gap
for civil infrastructure. However, identification of the desired
scenarios for the closure of the financing gap is complex because there
are many factors that affect investment in infrastructure. Thus, comprehensive models are required to (1)simulate the impacts of
policies, and (2)identify the highly likely scenarios for desired policy
outcomes. The objective of this paper is to create a simulation model
for ex-ante analysis of financing policies in highway transportation
infrastructure in the United States. Using the agent-based technique, this model simulates the microbehaviors of state Departments of
Transportation, private institutional investors, and the public. Using
the output of the simulation model, financing landscapes of the U.S.
transportation infrastructure are developed. The simulated landscape is
shown to be helpful in identifying the highly likely scenarios leading
to a high level of investment in highway transportation infrastructure
under the existing infrastructure investment structures and budget
constraints in the United States. The study presented in this paper is
novel with respect to (1)the application of the system-of-systems
modeling in the analysis of transportation infrastructure financing
policies, (2)identification of the desired policy scenarios and their
likelihoods for closure of the financing gap in the presence of
uncertainties and adaptive behaviors, and (3)simulation and
visualization of the impacts of financing policies at the state and
national levels. The model promotes a data-driven policy analysis and
provides policymakers with a tool to simultaneously account for the
impacts of several factors and uncertainties. (C) 2015 American Society
of Civil Engineers.
Tags
Construction management
Framework
Ideas