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000725012 019__ $$a903965925$$a908088913
000725012 020__ $$a9783319116747$$qelectronic book
000725012 020__ $$a3319116746$$qelectronic book
000725012 020__ $$z9783319116730
000725012 0247_ $$a10.1007/978-3-319-11674-7$$2doi
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000725012 049__ $$aISEA
000725012 050_4 $$aHE336.T7
000725012 08204 $$a388.3/1$$223
000725012 24500 $$aGame theoretic analysis of congestion, safety and security$$h[electronic resource] :$$btraffic and transportation theory /$$cKjell Hausken, Jun Zhuang, editors.
000725012 264_1 $$aCham :$$bSpringer,$$c2015.
000725012 300__ $$a1 online resource (xii, 220 pages) :$$billustrations (some color).
000725012 336__ $$atext$$btxt$$2rdacontent
000725012 337__ $$acomputer$$bc$$2rdamedia
000725012 338__ $$aonline resource$$bcr$$2rdacarrier
000725012 4901_ $$aSpringer Series in Reliability Engineering,$$x1614-7839
000725012 504__ $$aIncludes bibliographical references and indexes.
000725012 5050_ $$aPreface; Acknowledgments; Contents; 1 Congestion Management in Motorways and Urban Networks Through a Bargaining-Game-Based Coordination Mechanism; Abstract; 1 Introduction; 2 Non-linear Distributed Model Predictive Control: Bargaining Game Approach; 2.1 Problem Statement; 2.2 The Distributed Model Predictive Control Game; 3 Bargaining-Game-Based Coordination for Congestion Management on Motorways; 3.1 Motorway Traffic Model; 3.2 Bargaining-Game Approach to Congestion Management on Motorways; 3.3 Simulation and Results; 4 Bargaining-Game-Based Coordination for Urban Congestion Management
000725012 5058_ $$a4.1 Urban Traffic Model4.2 Bargaining-Game Approach to Congestion Management in Urban Traffic; 4.3 Simulation and Results; 4.4 Disagreement Point Analysis; 5 Conclusion; Acknowledgments; References; 2 Advanced Information Feedback Coupled with an Evolutionary Game in Intelligent Transportation Systems; Abstract; 1 Introduction; 2 The Models and Feedback Strategies; 2.1 Notations; 2.2 Evolutionary Game Theory; 2.3 The NS Mechanism; 2.4 Two-Route Model and Exit Scenario; 2.4.1 Two-Route Scenario; 2.4.2 Exit Scenario; 2.5 Related Definitions; 3 Simulation Results
000725012 5058_ $$a3.1 Advanced Information Feedback in a 1-2-1 Route ITS3.2 Evolutionary Game Coupled with the NS Model in a 1-2-1 Route ITS; 4 Conclusion; Acknowledgments; References; 3 Solving a Dynamic User-Optimal Route Guidance Problem Based on Joint Strategy Fictitious Play; Abstract; 1 Introduction; 2 User-Optimal Route Guidance Problem; 2.1 Problem Formulation; 2.2 Traffic Flow Model and Link Travel Time Prediction; 2.3 Iterative Solution Algorithm Based on the MSA; 3 Joint Strategy Fictitious Play for Dynamic User-Optimal Route Guidance Problem; 3.1 Fictitious Play
000725012 5058_ $$a3.2 Distributed Joint Strategy Fictitious Play Algorithm Under Information Provision4 Numerical Study; 4.1 Computational Results; 5 Conclusions; Acknowledgments; References; 4 A Psycho-Social Agent-Based Model of Driver Behavior Dynamics; Abstract; 1 Introduction; 2 Holistic-Emergent Social Interaction-Oriented Dynamics (HESIOD) Model; 3 Control Dimensions and Communication Topologies; 4 Results; 5 Concluding Remarks and Further Issues; References; 5 Game-Theoretic Context and Interpretation of Kerner's Three-Phase Traffic Theory; Abstract; 1 Introduction
000725012 5058_ $$a2 Four Classical Developments in Traffic Theory3 Kerner's Empirically Based Theory; 4 Common Games in Traffic Theory; 4.1 Two-Player Traffic Games; 4.1.1 Two-Player Chicken Game; 4.1.2 Two-Player Battle of the Sexes; 4.1.3 Two-Player Prisoner's Dilemma; 4.1.4 Two-Player Coordination Game; 4.2 n-Player Traffic Games; 4.2.1 n-Player Chicken Game; 4.2.2 n-Player Battle of the Sexes; 4.2.3 n-Player Prisoner's Dilemma; 4.2.4 n-Player Coordination Game; 5 Linking the Four Classical Developments with Game Theory; 6 Linking Kerner's Three-Phase Traffic Theory with Game Theory; 7 Conclusion
000725012 506__ $$aAccess limited to authorized users.
000725012 520__ $$aMaximizing reader insights into the interactions between game theory, excessive crowding and safety and security elements in traffic and transportation theory, this book establishes a new research angle by illustrating linkages between different research approaches and through laying the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs ? which may be in parallel, series, interlinked, or interdependent, with flows one way or both ways ? this book puts forward new congestion models, breaking new ground by introducing game theory and safety/security. Addressing the multiple actors who may hold different concerns regarding system reliability; e.g. one or several terrorists, a government, various local or regional government agencies, or others with stakes for or against system reliability, this book describes how governments authorities, and others may have the tools to handle congestion, but that these tools need to be improved whilst additionally ensuring safety and security against various threats. This game-theoretic analysis sets this book apart from the current congestion literature and ensures that the book will be of use to postgraduates, researchers, 3rd/4th-year undergraduates, policy makers, and practitioners.
000725012 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 14, 2015).
000725012 650_0 $$aTraffic flow$$xMathematical models.
000725012 650_0 $$aGame theory.
000725012 650_0 $$aTraffic congestion$$xMathematical models.
000725012 7001_ $$aHausken, Kjell,$$eeditor.
000725012 7001_ $$aZhuang, Jun,$$eeditor.
000725012 77608 $$iPrint version:$$z9783319116730
000725012 830_0 $$aSpringer series in reliability engineering.
000725012 852__ $$bebk
000725012 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-11674-7$$zOnline Access$$91397441.1
000725012 909CO $$ooai:library.usi.edu:725012$$pGLOBAL_SET
000725012 980__ $$aEBOOK
000725012 980__ $$aBIB
000725012 982__ $$aEbook
000725012 983__ $$aOnline
000725012 994__ $$a92$$bISE