Home
Resource
Emergency modeling in transportation via queuing and game theory
PDF
PDF format is widely accepted and good for printing.
Plug-in required
PDF-1(1.13 MB)
Citation & Export
View Usage Statistics
Staff View

Citation & Export
Hide

Simple citation

Duan, Zhe. Emergency modeling in transportation via queuing and game theory. Retrieved from https://doi.org/doi:10.7282/T3930RV7

Export

Click here for information about Citation Management Tools at Rutgers.

Statistics
Hide

Description

TitleEmergency modeling in transportation via queuing and game theory
NameDuan, Zhe (author); Baykal-Gürsoy, Melike (chair); Jafari, Mohsen A. (internal member); Özel, Tuğrul (internal member); Boros, Endre (outside member); Maher, Ali (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2013
Other Date2013-01 (degree)
SubjectIndustrial and Systems Engineering, Traffic congestion--Management, Emergency management, Game theory--Computer programs, Markov processes
Extentix, 94 p. : ill.
DescriptionIn modern transportation network, emergencies on roadway and man-made emergencies in the infrastructure can incur enormous costs to society directly and indirectly. The direct costs include transportation cost due to incident delay and traffic congestion, and various risks brought upon the infrastructure by man-made emergencies. The indirect cost can include economic and psychological impacts on society. Emergencies on roadways include accidents, disabled vehicles, adverse weather conditions, spilled loads, hazardous materials, etc. Under these cases, non-recurrent congestion will slow down the traffic flow on certain road link. In previous research, deterministic queuing models are often used for traffic flow modeling. However, due to the random environment of traffic flow, it is necessary to introduce stochastic elements into current traffic flow modeling. In our research, we use stochastic queuing models, such as Markov-modulated queuing systems, for traffic flow modeling under incidents. And non-recurrent and recurrent congestion models will be combined together to improve travel time estimation. Man-made emergencies in the infrastructure are terrorist attacks, suicide bombings, etc. Human casualties are the major goal of intelligent adversaries. We use game theory in order to allocate first responders' resources inside the transit infrastructure to minimize human casualty. In the static zero-sum game model, we show that both the adversary and the first responder choose the same group of locations to attack and defend. In the dynamic case when the first responder is mobile while the adversary is hidden in a cell, the equilibrium solution for the first responder becomes the best patrol policy within the infrastructure. This model utilizes partially observable Markov decision process (POMDP) in which the payoff functions depend on an exogenous people flow, thus, are time varying. People flow are modeled as an open queuing network in the infrastructure. And illustration example is shown to provide insight into the competitive nature of this game between first responder and adversary.
NotePh.D.
NoteIncludes bibliographical references
Noteby Zhe Duan
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3930RV7
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Version 8.5.5
Rutgers University Libraries - Copyright ©2024