Intelligent and automated transport system technology Books

Book SynopsisOver the last 20 years, the role of unmanned aircraft systems in modern warfare has grown at an unprecedented rate. No longer simply used for intelligence, data collection or reconnaissance, drones are routinely used for target acquisition and to strike enemy targets with missiles and bombs. Organized by nationality, Military Drones offers a compact guide to the main unmanned aerial vehicles being flown in combat zones today. These include classics, such as the MQ-1 Predator, primarily used for intelligence gathering; the Black Hornet Nano, a micro UAV that is so small it can fit in the palm of your hand and is used by ground troops for local situational awareness; the Chinese tri-copter Scorpion, which is ideal for the stationary observation and strike role in a built-up area; and the French EADS Talarion, a twinjet long-endurance UAV designed for high-altitude surveillance. Illustrated with more than 100 photographs and artworks, Military Drones provides a detailed insight into the specialist military unmanned aerial vehicles that play a key role in the modern battle space.Table of ContentsContents include: 1. United States Former Interstate TDR MQ-1 Predator RQ-2 Pioneer MQ-5 Hunter RQ-14 Dragon Eye RQ-16 T-Hawk FQM-151 Pointer CQ-24A K-MAX Desert Hawk Current MQ-1C Gray Eagle RQ-4 Global Hawk MQ-4C Triton RQ-7 Shadow MQ-8B Fire Scout/MQ-8C Fire Scout MQ-9 Reaper CQ-10 Snowgoose RQ-11 Raven RQ-12 Wasp MQ-19 Aerosonde RQ-20 Puma RQ-21 Blackjack RQ-170 Sentinel RQ-180 Black Hornet Nano Coyote Snipe NAV Switchblade Maveric Stalker ScanEagle Northrop Grumman Bat Future MQ-25 Stingray UAE ADCOM Systems United 40 Iran HESA Qasef-1 IAIO Fotros (Fallen Angel) Kian China Aisheng ASN-209 (Silver Eagle) AVIC Cloud Shadow AVIC WZ-8 CASC CH-5 Rainbow CASC CH-7 CASIC Skyhawk (series) Chengdu (AVIC) Soar Dragon (Soar Eagle) Gongji-11 (GJ-11) Hongdu Lijian (Sharp Sword) NORINCO Sharp Eye III Shenyang (AVIC) Divine Eagle Tengoen TB-001 Twin-Tailed Scorpion Ziyan Blowfish South Korea KARI TR-60 India DRDO AURA DRDO Rustom (Warrior) France Airbus DS Tanan 300 Airbus Helicopters VSR700 Dassault nEUROn EADS Talarion SAGEM Patroller Italy Leonardo Falco Xplorer Piaggio P.1HH Hammerhead South Africa Denel Dynamics Bateleur Israel Aeronautics Defense Dominator XP Aeronautics Defense Orbiter (series) Elbit Skystriker IAI Green Dragon IAI ROTEM L UVision Hero-900 Belarus ARP Golden Eagle Turkey Bayraktar Mini Bayraktar TB2 TAI Aksungur TAI Anka Germany Reiner Stemme Q01 UK BAe Magma BAe Systems Taranis Thales Watchkeeper WK450 Poland MALE Bayraktar TB2 RQ-7 Shadow 200 Orbiter BSL Orbiter 2 FlyEye Warmate circulating ammunition DragonFly Wizjer program PGZ-19R FT-5 FLIR Black Hornet MayFly system BSP Watchkeeper Russia Forpost ISR Kamov Ka-175 Kronstadt Orion-E Mikoyan Skat Rostech (Luch) Korsar Rostech Chirok (Teal) Sokol Altius Sukhoi Zond (Series) VR-Technologies VRT300 ZAO ENIX Eleron-3 (Aileron-3) Sweden UMS V-200 (Skeldar) Ukraine Antonov Horlytsya Skyeton Raybird-3

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Book SynopsisElectro - mobility is the number one topic when it comes to our mobility in the future. What does the vision of the BMW Group, Germany’s main pioneer in the field, l ook like? For the first time providing extensive insight into BMW’s workshop of ideas, this volume presents the multi - faceted concept for sustainable and visionary mobility right up to autonomous driving. In the spring of 2008, a think tank of engineers, d esigners, trend researchers, and financial experts met on a factory floor of BMW’s parent plant in Munich to rethink mobility. This volume traces the exciting venture in its complex development, while also looking at the future. A main focus is on the major challenges of our time — climate change, scarcity of resources, megacities — and the solution approaches: technological innovations, networked mobility, and the use of renewable materials. Autonomous driving plays a particularl y important role. Terrific close - ups and design drawings present all models from the BMW i3 and the BMW i8 to the BMW i Vision Future Interaction.

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Book SynopsisThis text outlines the concepts of modern control theory applied to the design and analysis of general flight control systems in a concise and mathematically rigorous style. It presents a comprehensive treatment of atmospheric and space flight control systems including aircraft, rockets and entry vehicles and spacecraft.Table of ContentsSeries Preface xiii Preface xv 1 Introduction 1 1.1 Notation and Basic Definitions 1 1.2 Control Systems 3 1.2.1 Linear Tracking Systems 7 1.2.2 Linear Time-Invariant Tracking Systems 9 1.3 Guidance and Control of Flight Vehicles 10 1.4 Special Tracking Laws 13 1.4.1 Proportional Navigation Guidance 13 1.4.2 Cross-Product Steering 16 1.4.3 Proportional-Integral-Derivative Control 19 1.5 Digital Tracking System 24 1.6 Summary 25 Exercises 26 References 28 2 Optimal Control Techniques 29 2.1 Introduction 29 2.2 Multi-variable Optimization 31 2.3 Constrained Minimization 33 2.3.1 Equality Constraints 34 2.3.2 Inequality Constraints 38 2.4 Optimal Control of Dynamic Systems 41 2.4.1 Optimality Conditions 43 2.5 The Hamiltonian and the Minimum Principle 44 2.5.1 Hamilton–Jacobi–Bellman Equation 45 2.5.2 Linear Time-Varying System with Quadratic Performance Index 47 2.6 Optimal Control with End-Point State Equality Constraints 48 2.6.1 Euler–Lagrange Equations 50 2.6.2 Special Cases 50 2.7 Numerical Solution of Two-Point Boundary Value Problems 52 2.7.1 Shooting Method 54 2.7.2 Collocation Method 57 2.8 Optimal Terminal Control with Interior Time Constraints 61 2.8.1 Optimal Singular Control 62 2.9 Tracking Control 63 2.9.1 Neighboring Extremal Method and Linear Quadratic Control 64 2.10 Stochastic Processes 69 2.10.1 Stationary Random Processes 75 2.10.2 Filtering of Random Noise 77 2.11 Kalman Filter 77 2.12 Robust Linear Time-Invariant Control 81 2.12.1 LQG/LTR Method 82 2.12.2 H2/H?E?E Design Methods 89 2.13 Summary 96 Exercises 98 References 101 3 Optimal Navigation and Control of Aircraft 103 3.1 Aircraft Navigation Plant 104 3.1.1 Wind Speed and Direction 110 3.1.2 Navigational Subsystems 112 3.2 Optimal Aircraft Navigation 115 3.2.1 Optimal Navigation Formulation 116 3.2.2 Extremal Solution of the Boundary-Value Problem: Long-Range Flight Example 119 3.2.3 Great Circle Navigation 121 3.3 Aircraft Attitude Dynamics 128 3.3.1 Translational and Rotational Kinetics 132 3.3.2 Attitude Relative to the Velocity Vector 135 3.4 Aerodynamic Forces and Moments 136 3.5 Longitudinal Dynamics 139 3.5.1 Longitudinal Dynamics Plant 142 3.6 Optimal Multi-variable Longitudinal Control 145 3.7 Multi-input Optimal Longitudinal Control 147 3.8 Optimal Airspeed Control 148 3.8.1 LQG/LTR Design Example 149 3.8.2 H?E?E Design Example 160 3.8.3 Altitude and Mach Control 166 3.9 Lateral-Directional Control Systems 173 3.9.1 Lateral-Directional Plant 173 3.9.2 Optimal Roll Control 177 3.9.3 Multi-variable Lateral-Directional Control: Heading-Hold Autopilot 180 3.10 Optimal Control of Inertia-Coupled Aircraft Rotation 183 3.11 Summary 189 Exercises 192 References 194 4 Optimal Guidance of Rockets 195 4.1 Introduction 195 4.2 Optimal Terminal Guidance of Interceptors 195 4.3 Non-planar Optimal Tracking System for Interceptors: 3DPN 199 4.4 Flight in a Vertical Plane 208 4.5 Optimal Terminal Guidance 211 4.6 Vertical Launch of a Rocket (Goddard’s Problem) 216 4.7 Gravity-Turn Trajectory of Launch Vehicles 219 4.7.1 Launch to Circular Orbit: Modulated Acceleration 220 4.7.2 Launch to Circular Orbit: Constant Acceleration 227 4.8 Launch of Ballistic Missiles 228 4.8.1 Gravity-Turn with Modulated Forward Acceleration 232 4.8.2 Modulated Forward and Normal Acceleration 233 4.9 Planar Tracking Guidance System 237 4.9.1 Stability, Controllability, and Observability 241 4.9.2 Nominal Plant for Tracking Gravity-Turn Trajectory 243 4.10 Robust and Adaptive Guidance 247 4.11 Guidance with State Feedback 250 4.11.1 Guidance with Normal Acceleration Input 250 4.12 Observer-Based Guidance of Gravity-Turn Launch Vehicle 254 4.12.1 Altitude-Based Observer with Normal Acceleration Input 255 4.12.2 Bi-output Observer with Normal Acceleration Input 260 4.13 Mass and Atmospheric Drag Modeling 266 4.14 Summary 274 Exercises 275 References 275 5 Attitude Control of Rockets 277 5.1 Introduction 277 5.2 Attitude Control Plant 277 5.3 Closed-Loop Attitude Control 281 5.4 Roll Control System 281 5.5 Pitch Control of Rockets 282 5.5.1 Pitch Program 282 5.5.2 Pitch Guidance and Control System 283 5.5.3 Adaptive Pitch Control System 288 5.6 Yaw Control of Rockets 294 5.7 Summary 295 Exercises 295 Reference 296 6 Spacecraft Guidance Systems 297 6.1 Introduction 297 6.2 Orbital Mechanics 297 6.2.1 Orbit Equation 298 6.2.2 Perifocal and Celestial Frames 299 6.2.3 Time Equation 301 6.2.4 Lagrange’s Coefficients 304 6.3 Spacecraft Terminal Guidance 305 6.3.1 Minimum Energy Orbital Transfer 307 6.3.2 Lambert’s Theorem 311 6.3.3 Lambert’s Problem 313 6.3.4 Lambert Guidance of Rockets 322 6.3.5 Optimal Terminal Guidance of Re-entry Vehicles 327 6.4 General Orbital Plant for Tracking Guidance 334 6.5 Planar Orbital Regulation 339 6.6 Optimal Non-planar Orbital Regulation 345 6.7 Summary 352 Exercises 352 References 355 7 Optimal Spacecraft Attitude Control 357 7.1 Introduction 357 7.2 Terminal Control of Spacecraft Attitude 357 7.2.1 Optimal Single-Axis Rotation of Spacecraft 358 7.3 Multi-axis Rotational Maneuvers of Spacecraft 364 7.4 Spacecraft Control Torques 375 7.4.1 Rocket Thrusters 375 7.4.2 Reaction Wheels, Momentum Wheels and Control Moment Gyros 377 7.4.3 Magnetic Field Torque 378 7.5 Satellite Dynamics Plant for Tracking Control 379 7.6 Environmental Torques 380 7.6.1 Gravity-Gradient Torque 382 7.7 Multi-variable Tracking Control of Spacecraft Attitude 383 7.7.1 Active Attitude Control of Spacecraft by Reaction Wheels 385 7.8 Summary 389 Exercises 389 References 390 Appendix A: Linear Systems 391 A.1 Definition 391 A.2 Linearization 392 A.3 Solution to Linear State Equations 392 A.3.1 Homogeneous Solution 393 A.3.2 General Solution 393 A.4 Linear Time-Invariant System 394 A.5 Linear Time-Invariant Stability Criteria 395 A.6 Controllability of Linear Time-Invariant Systems 395 A.7 Observability of Linear Time-Invariant Systems 395 A.8 Transfer Matrix 396 A.9 Singular Value Decomposition 396 A.10 Linear Time-Invariant Control Design 397 A.10.1 Regulator Design by Eigenstructure Assignment 397 A.10.2 Regulator Design by Linear Optimal Control 398 A.10.3 Linear Observers and Output Feedback Compensators 398 References 400 Appendix B: Stability 401 B.1 Preliminaries 401 B.2 Stability in the Sense of Lagrange 402 B.3 Stability in the Sense of Lyapunov 404 B.3.1 Asymptotic Stability 406 B.3.2 Global Asymptotic Stability 406 B.3.3 Lyapunov’s Theorem 407 B.3.4 Krasovski’s Theorem 408 B.3.5 Lyapunov Stability of Linear Systems 408 References 408 Appendix C: Control of Underactuated Flight Systems 409 C.1 Adaptive Rocket Guidance with Forward Acceleration Input 409 C.2 Thrust Saturation and Rate Limits (Increased Underactuation) 415 C.3 Single- and Bi-output Observers with Forward Acceleration Input 417 References 432 Index 433

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Book SynopsisNick Lambert is co-founder and director of NLA, a Blue Economy solutions company, which specializes in the Blue Economy and tech innovation in associated domains. He advises corporates on a wide range of marine and maritime issues, and regularly hosts and delivers keynote speeches at high-profile conferences.Andy Hamflett is co-founder and director of NLA and a journalist, researcher and innovation expert on new technologies. He leads innovative research projects that explore the emerging potential of Big Data for social impact. Jonathan Turner is co-founder and director of NLA and specializes in customer-focused organizational process design, lean methodology and performance measurement through analytical skills and practical use of data.Trade Review"Revealing and insightful, this book shares inspiring examples of innovations applied across a broad spectrum of Blue Economy sectors. These ideas are real and impactful and underline the importance of technology and creativity as an enabler for sustainable environments and economic growth." * David Loosley, Chief Executive, The Institute of Marine Engineering, Science and Technology *"A fascinating guide to how technology will shape the future of the Blue Economy, this book is essential reading for those looking to understand how the smart use of our oceans can support sustainable development." * Professor Dickon Howell, Director, Howell Marine Consulting, UK *"This book presents a compelling overview of the impressive range of technology innovation underpinning progress in sectors as diverse as sustainable fisheries, ocean tourism, smart port cities, shipping and seabed mapping. Start-ups and tech developers in all sectors could learn from the up-to-the-minute case studies presented in this thoroughly researched and well written book." * Tony Hughes, Dealmaker, Global Entrepreneur Programme – the UK’s Department for International Trade *"Here, at last, is a book that sets out the scale of challenges and opportunities that our oceans present, by three authors bringing enormous knowledge to the domain. The Blue Economy is so much more diverse than the traditional marine and maritime sectors, and this book is a must-read for anyone interested to understand where the Blue Economy is heading." * Dr. Jonathan Williams, CEO, Marine South East, UK *"The breadth of innovation across the blue economy is extraordinary. Andy, Nick and Jonathan have explored, sector by sector, to reveal insights and applications that are revolutionising industries and opening doors for new commercial opportunities in the seas and oceans." * Aidan Thorn, Maritime Innovation Expert *Table of Contents Chapter - 01: An introduction to the blue economy; Chapter - 02: Shipping; Chapter - 03: Ports and harbours; Chapter - 04: Offshore renewables; Chapter - 05: The cruise industry; Chapter - 06: Maritime surveillance; Chapter - 07: Aquaculture; Chapter - 08: Hydrography and bathymetry; Chapter - 09: Ocean observation; Chapter - 10: Sustainable fisheries; Chapter - 11: Subsea monitoring; Chapter - 12: Safety of life at sea; Chapter - 13: Conclusion

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Book SynopsisShows how planning land uses and transportation together with transportation demand management (TDM) policies creates safer, more walkable environments. TDM encourages travellers to maximize use of available transportation systems in the most efficient and effective ways possible.

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Book SynopsisThis book covers different aspects of Internet of Drones (IoD) including fundamentals in drone design, deployment challenges, and development of applications. It starts with a detailed description of concepts and processes in designing an efficient system, and architecture. It details different applications of IoD and its implementations in smart cities, agriculture, health care, defense, security, logistics, GIS mapping, and so forth. Recent developments in IoD design, application of AI techniques, case studies, and future directions are covered.Features: Focuses on important perspectives of the Internet of Drones (IoD) Emphasizes drone deployment in smart cities, smart agriculture, smart health care, and 3D mapping Covers challenges in drone design for applications with security and privacy issues Reviews diversified drone applications with real-use cases from modern drone players ranging from start-up companies to big giants in the dTable of Contents1. Internet Of Drones: Applications, Challenges, Opportunities. 2. Modelling, Simulation, and Analysis Hybrid Unmanned Aerial Vehicle with C-Wing. 3. Influence of Machine Learning Technique in Unmanned Aerial Vehicle. 4. Review of Medical Drones in Healthcare Applications. 5. CoVacciDrone: An Algorithmic-Drone-Based COVID-19 Vaccine Distribution Strategy. 6. Ambulance Drone for Rescue - A Perspective on Conceptual Design, Life Detection Systems, and Prototype Development. 7. A Comprehensive Review on Internet of Agro Drones for Precision Agriculture. 8. A Smart WeeDrone for Sustainable Agriculture. 9. Internet of Agro Drones for Precision Agriculture. 10. IOD-Enabled Swarm of Drones for Air Space Control. 11. Drones for Disaster Response and Management.

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Book SynopsisThis text explores formation control of vehicle systems and introduces three representative systems: space systems, aerial systems and robotic systems Formation Control of Multiple Autonomous Vehicle Systems offers a review of the core concepts of dynamics and control and examines the dynamics and control aspects of formation control in order to study a wide spectrum of dynamic vehicle systems such as spacecraft, unmanned aerial vehicles and robots. The text puts the focus on formation control that enables and stabilizes formation configuration, as well as formation reconfiguration of these vehicle systems. The authors develop a uniform paradigm of describing vehicle systems' dynamic behaviour that addresses both individual vehicle's motion and overall group's movement, as well as interactions between vehicles. The authors explain how the design of proper control techniques regulate the formation motion of these vehicles and the development of a system level decision-making strategyTable of ContentsPreface xiii List of Tables xvii List of Figures xix Acknowledgments xxv Part I Formation Control: Fundamental Concepts 1 1 Formation Kinematics 3 1.1 Notation 3 1.2 Vectorial Kinematics 5 1.2.1 Frame Rotation 5 1.2.2 The Motion of a Vector 7 1.2.3 The First Time Derivative of a Vector 11 1.2.4 The Second Time Derivative of a Vector 12 1.2.5 Motion with Respect to Multiple Frames 12 1.3 Euler Parameters and Unit Quaternion 13 2 Formation Dynamics of Motion Systems 17 2.1 Virtual Structure 17 2.1.1 Formation Control Problem Statement 19 2.1.2 Extended Formation Control Problem 22 2.2 Behaviour-based Formation Dynamics 26 2.3 Leader–Follower Formation Dynamics 27 3 Fundamental Formation Control 29 3.1 Unified Problem Description 29 3.1.1 Some Key Definitions for Formation Control 29 3.1.2 A Simple Illustrative Example 30 3.2 Information Interaction Conditions 32 3.2.1 Algebraic GraphTheory 32 3.2.2 Conditions for the Case without a Leader 33 3.2.3 Conditions for the Case with a Leader 35 3.3 Synchronization Errors 36 3.3.1 Local Synchronization Error: Type I 37 3.3.2 Local Synchronization Error: Type II 38 3.3.3 Local Synchronization Error: Type III 40 3.4 Velocity Synchronization Control 42 3.4.1 Velocity Synchronization without a Leader 42 3.4.2 Velocity Synchronization with a Leader 43 3.5 Angular-position Synchronization Control 45 3.5.1 Synchronization without a Position Reference 45 3.5.2 Synchronization to a Position Reference 47 3.6 Formation via Synchronized Tracking 48 3.6.1 Formation Control Solution 1 50 3.6.2 Formation Control Solution 2 51 3.7 Simulations 52 3.7.1 Verification of Theorem 3.12 52 3.7.2 Verification of Theorem 3.13 54 3.7.3 Verification of Theorem 3.14 57 3.8 Summary 60 Bibliography for Part I 61 Part II Formation Control: Advanced Topics 63 4 Output-feedback Solutions to Formation Control 65 4.1 Introduction 65 4.2 Problem Statement 65 4.3 Linear Output-feedback Control 66 4.4 Bounded Output-feedback Control 68 4.5 Distributed Linear Control 71 4.6 Distributed Bounded Control 72 4.7 Simulations 73 4.7.1 Case 1: Verification of Theorem 4.1 73 4.7.2 Case 2: Verification of Theorem 4.5 76 4.8 Summary 78 5 Robust and Adaptive Formation Control 81 5.1 Problem Statement 81 5.2 Continuous Control via State Feedback 83 5.2.1 Controller Development 83 5.2.2 Analysis of Tracker u0i84 5.2.3 Design of Disturbance Estimators 85 5.2.4 Closed-loop Performance Analysis 87 5.3 Bounded State Feedback Control 90 5.3.1 Design of Bounded State Feedback 90 5.3.2 Robustness Analysis 92 5.3.3 The Effect of UDE on Stability 94 5.3.4 The Effect of UDE on the Bounds of Control 94 5.4 Continuous Control via Output Feedback 95 5.4.1 Design of u0i and d^i 95 5.4.2 Stability Analysis 96 5.5 Discontinuous Control via Output Feedback 97 5.5.1 Controller Design 98 5.5.2 Stability Analysis 100 5.6 GSE-based Synchronization Control 102 5.6.1 Coupled Errors 103 5.6.2 Controller Design and Convergence Analysis 105 5.7 GSE-based Adaptive Formation Control 108 5.7.1 Problem Statement 108 5.7.2 Controller Development 109 5.8 Summary 111 Bibliography for Part II 113 Part III Formation Control: Case Studies 115 6 Formation Control of Space Systems 117 6.1 Lagrangian Formulation of Spacecraft Formation 117 6.1.1 Lagrangian Formulation 117 6.1.2 Attitude Dynamics of Rigid Spacecraft 118 6.1.3 Relative Translational Dynamics 120 6.2 Adaptive Formation Control 122 6.3 Applications and Simulation Results 123 6.3.1 Application 1: Leader–Follower Spacecraft Pair 123 6.3.1.1 Simulation Condition 123 6.3.1.2 Control Parameters 123 6.3.1.3 Simulation Results and Analysis 124 6.3.2 Application 2: Multiple Spacecraft in Formation 124 6.4 Summary 130 7 Formation Control of Aerial Systems 131 7.1 Vortex-induced Aerodynamics 131 7.1.1 Model of the Trailing Vortices of Leader Aircraft 134 7.1.2 Single Horseshoe Vortex Model 135 7.1.3 Continuous Vortex Sheet Model 137 7.2 Aircraft Autopilot Models 138 7.2.1 Models for the Follower Aircraft 139 7.2.2 Kinematics for Close-formation Flight 140 7.3 Controller Design 140 7.3.1 Linear Proportional-integral Controller 140 7.3.2 UDE-based Formation-flight Controller 142 7.3.2.1 Formation Flight Controller Design 143 7.3.2.2 Uncertainty and Disturbance Estimator 144 7.4 Simulation Results 147 7.4.1 Simulation Results for Controller 1 147 7.4.2 Simulation Results for Controller 2 148 7.5 Summary 154 8 Formation Control of Robotic Systems 157 8.1 Introduction 157 8.2 Visual Tracking 159 8.2.1 Imaging Hardware 159 8.2.2 Image Distortion 160 8.2.3 Color Thresholding 163 8.2.4 Noise Rejection 163 8.2.5 Data Extraction 165 8.3 Synchronization Control 167 8.3.1 Synchronization 167 8.3.2 Formation Parameters 168 8.3.3 Architecture 169 8.3.4 Control Law 169 8.3.5 Simulations 170 8.3.5.1 Constant Formation along Circular Trajectory 171 8.3.5.2 Time-varying Formation along Linear Trajectory 173 8.4 Passivity Control 176 8.4.1 Passivity 176 8.4.2 Formation Parameters 176 8.4.3 Control Law 177 8.4.4 Simulation 178 8.5 Experiments 181 8.5.1 Setup 181 8.5.2 Results 182 8.5.2.1 Constant Formation along Circular Trajectory 182 8.5.2.2 Time-varying Formation along Linear Trajectory 183 8.6 Summary 186 Bibliography for Part III 189 Part IV Formation Control: Laboratory 191 9 Experiments on 3DOF Desktop Helicopters 193 9.1 Description of the Experimental Setup 193 9.2 MathematicalModels 196 9.2.1 Nonlinear 3DOF Model 196 9.2.2 2DOF Model for Elevation and Pitch Control 199 9.3 Experiment 1: GSE-based Synchronized Tracking 201 9.3.1 Objective 201 9.3.2 Initial Conditions and Desired Trajectories 202 9.3.3 Control Strategies 203 9.3.4 Disturbance Condition 203 9.3.5 Experimental Results 204 9.3.6 Summary 208 9.4 Experiment 2: UDE-based Robust Synchronized Tracking 208 9.4.1 Objective 208 9.4.2 Initial Conditions and Desired Trajectories 208 9.4.3 Control Strategies 209 9.4.4 Experimental Results and Discussions 210 9.4.5 Summary 215 9.5 Experiment 3: Output-feedback-based Sliding-mode Control 216 9.5.1 Objective 216 9.5.2 Initial Conditions and Desired Trajectories 216 9.5.3 Control Strategies 217 9.5.4 Experimental Results and Discussions 217 9.5.5 Summary 222 Bibliography for Part IV 223 Part V Appendix 225 Bibliography for Appendix 237 Index 239

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Book SynopsisWith the increasing worldwide trend in population migration into urban centers, we are beginning to see the emergence of the kinds of mega-cities which were once the stuff of science fiction. It is clear to most urban planners and developers that accommodating the needs of the tens of millions of inhabitants of those megalopolises in an orderly and uninterrupted manner will require the seamless integration of and real-time monitoring and response services for public utilities and transportation systems. Part speculative look into the future of the world's urban centers, part technical blueprint, this visionary book helps lay the groundwork for the communication networks and services on which tomorrow's smart cities will run. Written by a uniquely well-qualified author team, this book provides detailed insights into the technical requirements for the wireless sensor and actuator networks required to make smart cities a reality.Table of ContentsList of Contributors xxi Preface xxvii SECTION I Communication Technologies for Smart Cities 1 1 Energy-Harvesting Cognitive Radios in Smart Cities 3Mustafa Ozger, Oktay Cetinkaya and Ozgur B. Akan 1.1 Introduction 3 1.1.1 Cognitive Radio 5 1.1.2 Cognitive Radio Sensor Networks 5 1.1.3 Energy Harvesting and Energy-Harvesting Sensor Networks 6 1.2 Motivations for Using Energy-Harvesting Cognitive Radios in Smart Cities 6 1.2.1 Motivations for Spectrum-Aware Communications 7 1.2.2 Motivations for Self-Sustaining Communications 7 1.3 Challenges Posed by Energy-Harvesting Cognitive Radios in Smart Cities 8 1.4 Energy-Harvesting Cognitive Internet of Things 9 1.4.1 Definition 9 1.4.2 Energy-Harvesting Methods in IoT 10 1.4.3 System Architecture 12 1.4.4 Integration of Energy-Harvesting Cognitive Radios with the Internet 13 1.5 A General Framework for EH-CRs in the Smart City 14 1.5.1 Operation Overview 14 1.5.2 Node Architecture 15 1.5.3 Network Architecture 16 1.5.4 Application Areas 17 1.6 Conclusion 18 References 18 2 LTE-D2D Communication for Power Distribution Grid: Resource Allocation for Time-Critical Applications 21Leonardo D. Oliveira, Taufik Abrao and Ekram Hossain 2.1 Introduction 21 2.2 Communication Technologies for Power Distribution Grid 22 2.2.1 An Overview of Smart Grid Architecture 22 2.2.2 Communication Technologies for SG Applications Outside Substations 24 2.2.3 Communication Networks for SG 26 2.3 Overview of Communication Protocols Used in Power Distribution Networks 27 2.3.1 Modbus 27 2.3.2 IEC 60870 29 2.3.3 DNP3 31 2.3.4 IEC 61850 32 2.3.5 SCADA Protocols for Smart Grid: Existing State-of-the-Art 35 2.4 Power Distribution System: Distributed Automation Applications and Requirements 36 2.4.1 Distributed Automation Applications 36 2.4.1.1 Voltage/Var Control (VVC) 37 2.4.1.2 Fault Detection, Isolation, and Restoration (FDCIR) 38 2.4.2 Requirements for Distributed Automation Applications 39 2.5 Analysis of Data Flow in Power Distribution Grid 40 2.5.1 Model for Power Distribution Grid 40 2.5.2 IEC 61850 Traffic Model 42 2.5.2.1 Cyclic Data Flow 42 2.5.2.2 Stochastic Data Flow 45 2.5.2.3 Burst Data Flow 46 2.6 LTE-D2D for DA: Resource Allocation for Time-Critical Applications 47 2.6.1 Overview of LTE 47 2.6.2 IEC 61850 Protocols over LTE 48 2.6.2.1 Mapping MMS over LTE 49 2.6.2.2 Mapping GOOSE over LTE 50 2.6.3 Resource Allocation in uplink LTE-D2D for DA Applications 50 2.6.3.1 Problem Formulation 51 2.6.3.2 Scheduler Design 54 2.6.3.3 Numerical Evaluation 55 2.7 Conclusion 60 References 61 3 5G and Cellular Networks in the Smart Grid 69Jimmy Jessen Nielsen, Ljupco Jorguseski, Haibin Zhang, Hervé Ganem, Ziming Zhu and Petar Popovski 3.1 Introduction 69 3.1.1 Massive MTC 70 3.1.2 Mission-Critical MTC 70 3.1.3 Secure Mission-Critical MTC 71 3.2 From Power Grid to Smart Grid 71 3.3 Smart Grid Communication Requirements 74 3.3.1 Traffic Models and Requirements 74 3.4 Unlicensed Spectrum and Non-3GPP Technologies for the Support of Smart Grid 76 3.4.1 IEEE 802.11ah 76 3.4.2 Sigfox’s Ultra-Narrow Band (UNB) Approach 79 3.4.3 LoRaTM Chirp Spread Spectrum Approach 80 3.5 Cellular and 3GPP Technologies for the Support of Smart Grid 82 3.5.1 Limits of 3GPP Technologies up to Release 11 82 3.5.2 Recent Enhancements of 3GPP Technologies for IoT Applications (Releases 12–13) 83 3.5.2.1 LTE Cat-0 and Cat-M1 devices 84 3.5.2.2 Narrow-Band Internet of Things (NB-IoT) and Cat-NB1 Devices 85 3.5.3 Performance of Cellular LTE Systems for Smart Grids 86 3.5.4 LTE Access Reservation Protocol Limitations 87 3.5.4.1 LTE Access Procedure 87 3.5.4.2 Connection Establishment 90 3.5.4.3 Numerical Evaluation of LTE Random Access Bottlenecks 91 3.5.5 What Can We Expect from 5G? 93 3.6 End-to-End Security in Smart Grid Communications 94 3.6.1 Network Access Security 95 3.6.2 Transport Level Security 96 3.6.3 Application Level Security 96 3.6.4 End-to-End Security 96 3.6.5 Access Control 97 3.7 Conclusions and Summary 99 References 100 4 Machine-to-Machine Communications in the Smart City—a Smart Grid Perspective 103Ravil Bikmetov, M. Yasin Akhtar Raja and KhurramKazi 4.1 Introduction 103 4.2 Architecture and Characteristics of Smart Grids for Smart Cities 105 4.2.1 Definition of a Smart Grid and Its Conceptual Model 106 4.2.2 Standardization Approach in Smart Grids 112 4.2.3 Smart Grid Interoperability Reference Model (SGIRM) 113 4.2.4 Smart Grid Architecture Model 114 4.2.5 Energy Sources in the Smart Grid 115 4.2.6 Energy Consumers in a Smart Grid 117 4.2.7 Energy Service Providers in the Smart Grid 119 4.3 Intelligent Machine-to-Machine Communications in Smart Grids 120 4.3.1 Reference Architecture of Machine-to-Machine Interactions 120 4.3.2 Communication Media and Protocols 121 4.3.3 Layered Structure of Machine-to-Machine Communications 126 4.4 Optimization Algorithms for Energy Production, Distribution, and Consumption 132 4.5 Machine Learning Techniques in Efficient Energy Services and Management 134 4.6 Future Perspectives 135 4.7 Appendix 136 References 138 5 5G and D2D Communications at the Service of Smart Cities 147Muhammad Usman,Muhammad Rizwan Asghar and Fabrizio Granelli 5.1 Introduction 147 5.2 Literature Review 150 5.3 Smart City Scenarios 153 5.3.1 Public Health 154 5.3.2 Transportation and Environment 155 5.3.3 Energy Efficiency 157 5.3.4 Smart Grid 157 5.3.5 Water Management 158 5.3.6 Disaster Response and Emergency Services 159 5.3.7 Public Safety and Security 159 5.4 Discussion 160 5.4.1 Multiple Radio Access Technologies (Multi-RAT) 160 5.4.2 Virtualization 160 5.4.3 Distributed/Edge Computing 161 5.4.4 D2D Communication 161 5.4.5 Big Data 162 5.4.6 Security and Privacy 163 5.5 Conclusion 163 References 163 SECTION II Emerging Communication Networks for Smart Cities 171 6 Software Defined Networking and Virtualization for Smart Grid 173Hakki C. Cankaya 6.1 Introduction 173 6.2 Current Status of Power Grid and Smart Grid Modernization 174 6.2.1 Smart Grid 174 6.3 Network Softwarerization in Smart Grids 177 6.3.1 Software Defined Networking (SDN) as Next-Generation Software-Centric Approach to Telecommunications Networks 177 6.3.2 Adaptation of SDN for Smart Grid and City 179 6.3.3 Opportunities for SDN in Smart Grid 179 6.4 Virtualization for Networks and Functions 183 6.4.1 Network Virtualization 183 6.4.2 Network Function Virtualization 184 6.5 Use Cases of SDN/NFV in the Smart Grid 185 6.6 Challenges and Issues with SDN/NFV-Based Smart Grid 187 6.7 Conclusion 187 References 188 7 GHetNet: A Framework Validating Green Mobile Femtocells in Smart-Grids 191Fadi Al-Turjman 7.1 Introduction 191 7.2 RelatedWork 192 7.2.1 Static Validation Techniques 194 7.2.2 Dynamic Validation Techniques 195 7.3 System Models 197 7.3.1 Markov Model 199 7.3.2 Service-Rate Model 199 7.3.3 Communication Model 200 7.4 The Green HetNet (GHetNet) Framework 201 7.5 A Case Study: E-Mobility for Smart Grids 206 7.5.1 Performance metrics and parameters 207 7.5.2 Simulation Setups and Baselines 208 7.5.3 Results and Discussion 208 7.5.3.1 The Impact of Velocity on FBS Performance 209 7.5.3.2 The Impact of the Grid Load on Energy Consumption 211 7.6 Conclusion 213 References 213 8 Communication Architectures and Technologies for Advanced Smart Grid Services 217Francois Lemercier, Guillaume Habault, Georgios Z. Papadopoulos, Patrick Maille, NicolasMontavont and Periklis Chatzimisios 8.1 Introduction 217 8.2 The Smart Grid Communication Architecture and Infrastructure 219 8.2.1 DSO-Based Communications 220 8.2.1.1 The Existing AMI Organization 220 8.2.1.2 Communication Technologies used in the AMI 222 8.2.1.3 AMI Limitations 223 8.2.2 Internet-Based Architectures 224 8.2.2.1 IP-Based Architecture Limitations 225 8.2.3 Next-Generation Smart Grid Architecture 225 8.2.3.1 Technical Issues for Next-Generation Smart Grids 227 8.2.3.2 Handing Back the Keys to the User: Energy Management Should Be Separated from the Smart Meter 227 8.2.3.3 To Build an Open Market, Use an Open Network 228 8.2.3.4 Multi-Level Aggregation 228 8.2.3.5 Security Concerns 229 8.2.3.6 Ongoing Research Efforts 229 8.3 Routing Information in the Smart Grid 231 8.3.1 Routing Family of Protocols 231 8.3.1.1 Proactive Routing Protocol 232 8.3.1.2 Topology Management under RPL 232 8.3.1.3 Routing Table Maintenance under RPL 233 8.3.1.4 Routing Strategy: Metrics and Constraints 234 8.3.1.5 Path Computation under RPL 234 8.3.1.6 Summary of the RPL DODAG construction 235 8.3.1.7 Reactive Routing Protocol 236 8.3.1.8 Topology Management under AODV 237 8.3.2 Reactive Routing Protocol in a Constrained Network 238 8.3.2.1 Performance Evaluation 239 8.3.2.2 Summary on Routing Protocols 241 8.4 Conclusion 242 References 243 9 Wireless Sensor Networks in Smart Cities: Applications of Channel Bonding to Meet Data Communication Requirements 247Syed Hashim Raza Bukhari, Sajid Siraj andMubashir Husain Rehmani 9.1 Introduction, Basics, and Motivation 247 9.2 WSNs in Smart Cities 248 9.2.1 WSNs in Underground Transportation 249 9.2.2 WSNs in Smart Cab Services 249 9.2.3 WSNs in Waste Management Systems 249 9.2.4 WSNs in Atmosphere Health Monitoring 249 9.2.5 WSNs in Smart Grids 252 9.2.6 WSNs in Weather Forecasting 252 9.2.7 WSNs in Home Automation 252 9.2.8 WSNs in Structural Health Monitoring 252 9.3 Channel Bonding 253 9.3.1 Channel Bonding Schemes in Traditional Networks 253 9.3.2 Channel Bonding Schemes in Wireless Sensor Networks 254 9.3.3 Channel Bonding Schemes in Cognitive Radio Networks 255 9.3.4 Channel Bonding for Cognitive Radio Sensor Networks 257 9.4 Applications of Channel Bonding in CRSN-Based Smart Cities 258 9.4.1 CRSNs in Smart Health Care 258 9.4.2 CRSNs in M2M Communications 258 9.4.3 CRSNs Multiple Concurrent Deployments in Smart Cities 259 9.4.4 CRSNs in Smart Home Applications 259 9.4.5 CRSNs Smart Environment Control 259 9.4.6 CRSNs-Based IoT 259 9.5 Issues and Challenges Regarding the Implementation of Channel Bonding in Smart Cities 259 9.5.1 Privacy of Citizens 260 9.5.2 Energy Conservation 260 9.5.3 Data Storage and Aggregation 260 9.5.4 Geographic Awareness and Adaptation 260 9.5.5 Interference and Spectrum Issues 260 9.6 Conclusion 261 References 261 10 A Prediction Module for Smart City IoT Platforms 269Sema F. Oktug, Yusuf Yaslan and Halil Gulacar 10.1 Introduction 269 10.2 IoT Platforms for Smart Cities 271 10.2.1 ARM Mbed 271 10.2.2 Cumulocity 271 10.2.3 DeviceHive 273 10.2.4 Digi 273 10.2.5 Digital Service Cloud 274 10.2.6 FiWare 274 10.2.7 Global Sensor Networks (GSN) 274 10.2.8 IoTgo 274 10.2.9 Kaa 275 10.2.10 Nimbits 275 10.2.11 RealTime.io 275 10.2.12 SensorCloud 275 10.2.13 SiteWhere 276 10.2.14 TempoIQ 276 10.2.15 Thinger.io 276 10.2.16 Thingsquare 276 10.2.17 ThingWorx 277 10.2.18 VITAL 277 10.2.19 Xively 277 10.3 Prediction Module Developed 277 10.3.1 The VITAL IoT Platform 278 10.3.2 VITAL Prediction Module 278 10.4 AUse Case Employing the Traffic Sensors in Istanbul 281 10.4.1 Prediction Techniques Employed 282 10.4.1.1 Data Preprocessing 284 10.4.1.2 Feature Vectors 284 10.4.2 Results 285 10.4.2.1 Regression Results 286 10.5 Conclusion 288 Acknowledgment 288 References 289 SECTION III Renewable Energy Resources and Microgrid in Smart Cities 291 11 Integration of Renewable Energy Resources in the Smart Grid: Opportunities and Challenges 293Mohammad UpalMahfuz, Ahmed O. Nasif,MdMaruf Hossain andMd. Abdur Rahman 11.1 Introduction 293 11.2 The Smart Grid Paradigm 294 11.2.1 The Smart Grid Concept 294 11.2.2 System Components of the SG 296 11.3 Renewable Energy Integration in the Smart Grid 298 11.3.1 Resource Characteristics and Distributed Generation 298 11.3.2 Why Is Integration Necessary? 299 11.4 Opportunities and Challenges 299 11.4.1 Energy Storage (ES) 300 11.4.1.1 Key Energy Storage Technologies 300 11.4.1.2 Key Energy Storage Challenges in SG 301 11.4.2 Distributed Generation (DG) 302 11.4.2.1 Key DG Sources and Generators 303 11.4.2.2 Key Parts and Functions of a DG System and Its Distribution 303 11.4.2.3 DG and Dispatch Challenges 304 11.4.3 Resource Forecasting, Modeling, and Scheduling 305 11.4.3.1 Resource Modeling and Scheduling 305 11.4.3.2 Resource Forecasting (RF) 307 11.4.4 Demand Response 308 11.4.5 Demand-Side Management (DSM) 309 11.4.6 Monitoring 310 11.4.7 Transmission Techniques 311 11.4.8 System-Related Challenges 311 11.4.9 V2G Challenges 312 11.4.10 Security Challenges in the High Penetration of RE Resources 314 11.5 Case Studies 314 11.6 Conclusion 315 References 316 12 Environmental Monitoring for Smart Buildings 327Petros Spachos and Konstantinos Plataniotis 12.1 Introduction 327 12.2 Wireless Sensor Networks in Monitoring Applications 329 12.3 Application Requirements and Challenges 330 12.3.1 Monitoring Area 330 12.3.2 Application Scenario and Design Goal 332 12.3.3 Requirements 333 12.3.3.1 Sensor Type 333 12.3.3.2 Real-Time Data Aggregation 335 12.3.3.3 Scalability 335 12.3.3.4 Usability, Autonomy, and Reliability 336 12.3.3.5 Remote Management 336 12.3.4 Challenges 336 12.3.4.1 Power Management 336 12.3.4.2 Wireless Network Coexistence 337 12.3.4.3 Mesh Routing 337 12.3.4.4 Robustness 337 12.3.4.5 Dynamic Changes 337 12.3.4.6 Flexibility 337 12.3.4.7 Size and cost 337 12.4 Wireless Sensor Network Architecture 338 12.4.1 Framework 338 12.4.2 Hardware Infrastructure 339 12.4.3 Data Processing 341 12.4.3.1 Noise Reduction, Data Smoothing, and Calibration 341 12.4.3.2 Packet formation process 342 12.4.3.3 Information Processing and Storage 343 12.4.4 Indoor Monitoring System 343 12.5 Experiments and Results 343 12.5.1 Experimental Setup 343 12.5.2 Results Analysis 347 12.6 Conclusions 350 References 350 13 Cooperative EnergyManagement in Microgrids 355Ioannis Zenginis, John Vardakas, Prodromos-VasileiosMekikis and Christos Verikoukis 13.1 Introduction 355 13.2 The Cooperative Energy Management System Model 357 13.2.1 PV Panel Modeling 359 13.2.2 Energy Storage System 360 13.2.3 Inverter 361 13.2.4 Microgrid Energy Exchange 361 13.3 Evaluation and Discussion 362 13.4 Conclusion 366 Acknowledgment 367 References 368 14 Optimal Planning and Performance Assessment of Multi-Microgrid Systems in Future Smart Cities 371ShouxiangWang, LeiWu, Qi Liu and Shengxia Cai 14.1 Optimal Planning of Multi-Microgrid Systems 372 14.1.1 Introduction 372 14.1.2 Optimal Structure Planning 373 14.1.2.1 Definition of Indices 373 14.1.2.2 Structure Planning Method 375 14.1.3 Optimal Capacity Planning 377 14.1.3.1 Definition of Indexes 377 14.1.3.2 Capacity Planning Method 381 14.1.4 Conclusions 384 14.2 Performance Assessment of Multi-Microgrid System 384 14.2.1 Introduction 384 14.2.2 Comprehensive Evaluation Indexes 386 14.2.2.1 MMGS Source-Charge Capacity Index 386 14.2.2.2 MMGS Energy Interaction Index 388 14.2.2.3 MMGS Reliability Index 390 14.2.2.4 MMGS Economics Index 395 14.2.2.5 Energy Utilization Efficiency Index 398 14.2.2.6 Energy Saving and Emission Reduction Index 398 14.2.2.7 Renewable Energy Utilization Index 399 14.2.3 Performance Assessment 400 14.2.3.1 Performance Assessment of Grid-Connected MMGS 400 14.2.3.2 Performance Assessment of Islanded MMGS 401 14.2.3.3 Annual Performance Assessment of the MMGS 402 14.2.4 Case Studies 403 14.2.4.1 System Description 403 14.2.4.2 Numerical Results 403 14.3 Conclusions 406 Acknowledgment 407 References 407 SECTION IV Smart Cities, Intelligent Transportation Systemand Electric Vehicles 411 15 Wireless Charging for Electric Vehicles in the Smart Cities: Technology Review and Impact 413Alicia Triviño-Cabrera and José A. Aguado 15.1 Introduction 413 15.2 Review of theWireless Charging Methods 415 15.2.1 Technologies SupportingWireless Power Transfer for EVs 415 15.2.2 Operation Modes forWireless Power Transfer in EVs 416 15.3 Electrical Effect of Charging Technologies on the Grid 418 15.3.1 Harmonics Control in EVWireless Chargers 418 15.3.2 Power Factor Control in EVWireless Chargers 419 15.3.3 Implementation of Bidirectionality in EVWireless Chargers 420 15.3.4 Discussion 421 15.4 Scheduling Considering Charging Technologies 421 15.5 Conclusions and Future Guidelines 423 References 424 16 Channel Access Modelling for EV Charging/Discharging Service through Vehicular ad hoc Networks (VANETs) Communications 427Dhaou Said and Hussein T. Mouftah 16.1 Introduction 428 16.2 Technical Environment of the EV Charging/Discharging Process 428 16.2.1 EVSE Overview 429 16.2.2 Inductive Chargers: Opportunities and Potential 429 16.3 Overview of Communication Technologies in the Smart Grid 430 16.3.1 Power Line Communication 430 16.3.2 Wireless Communications for EV–Smart Grid Applications 431 16.4 Channel Access Model for EV Charging Service 432 16.4.1 Overview of VANET and LTE 432 16.4.2 Case Study: Access ChannelModel 433 16.4.3 Simulations Results 438 16.5 Conclusions 440 References 440 17 Intelligent Parking Management in Smart Citie s 443Sanket Gupte andMohamed Younis 17.1 Introduction 443 17.2 Design Issues and Taxonomy of Parking Solutions 445 17.2.1 Design Issues for Autonomous Parking Systems 445 17.2.2 Taxonomy of Parking Solutions 445 17.3 Classification of Existing Parking Systems 447 17.3.1 Sensing Infrastructure 447 17.3.2 Communication Infrastructure 457 17.3.3 Storage Infrastructure 460 17.3.4 Application Infrastructure 461 17.3.5 User Interfacing 463 17.3.6 Comparison of Existing Parking Systems 465 17.4 Participatory Sensing–Based Smart Parking 465 17.4.1 The Components 467 17.4.1.1 Users 467 17.4.1.2 IoT Devices 467 17.4.1.3 Server 468 17.4.1.4 Parking Spots 468 17.4.2 Parking Management Application 469 17.4.2.1 User Interface 469 17.4.2.2 Smart Reporting System 470 17.4.2.3 Leaderboard 470 17.4.2.4 Rewards Store 471 17.4.2.5 Enforcement and Compliance 472 17.4.2.6 External Integration 472 17.4.3 Data Processing and Cloud Support 472 17.4.3.1 Availability Computation 472 17.4.3.2 Reputation System 473 17.4.3.3 Scoring System 474 17.4.3.4 ReservationModel 474 17.4.3.5 Analysis and Learning 474 17.4.4 Implementation and Performance Evaluation 474 17.4.4.1 Prototype Application 474 17.4.4.2 Experiment Setup 475 17.4.4.3 Simulation Results 475 17.4.5 Features and Benefits 477 17.5 Conclusions and Future Advancements 479 References 480 18 Electric Vehicle Scheduling and Charging in Smart Cities 485Muhammmad Amjad, Mubashir Husain Rehmani and Tariq Umer 18.1 Introduction 485 18.1.1 Integration of EVs into Smart Cities 486 18.1.1.1 Enhancing the Existing Power Capacity 486 18.1.1.2 Designing the Communication Protocols to Support the Smart Recharging Structure 486 18.1.1.3 Development of a Well-designed Recharging Architecture 486 18.1.1.4 Considering the Expected Load on the Smart Grid 486 18.1.1.5 Need for Scheduling Approaches for EVs Recharging 486 18.1.2 Main Contributions 487 18.1.3 Organization of the Chapter 487 18.2 Smart Cities and Electric Vehicles: Motivation, Background, and ApplicationScenarios 488 18.2.1 Smart Cities: An Overview 488 18.2.1.1 Provision of Smart Transportation 488 18.2.1.2 Energy Management in Smart cities 488 18.2.1.3 Integration of the Economic and Business Model 488 18.2.1.4 Wireless Communication Needs/Communication Architectures for Smart Cities 489 18.2.1.5 Traffic Congestion Avoidance in Smart Cities 489 18.2.1.6 Support of Heterogeneous Technologies in Smart Cities 489 18.2.1.7 Green Applications Support in Smart Cities 489 18.2.1.8 Security and Privacy in Smart Cities 490 18.2.2 Motivation of Using EVs in Smart cities 490 18.2.3 Application Scenarios 490 18.2.3.1 Avoiding Spinning Reserves 490 18.2.3.2 V2G and G2V Capability 491 18.2.3.3 CO2 Minimization 491 18.2.3.4 Load Management on the Local Microgrid 491 18.3 EVs Recharging Approaches in Smart Cities 491 18.3.1 Centralized EVs Recharging Approach 491 18.3.1.1 Main Contributions and Limitations of Centralized EVs-Recharging Approach 492 18.3.2 Distributed EVs Recharging Approach 493 18.3.2.1 Main Contributions and Limitations of the Distributed EVs-recharging Approach 493 18.4 Scheduling EVs Recharging in Smart Cities 493 18.4.1 Objectives Achieved via Different Scheduling Approaches 494 18.4.1.1 Reduction of Power Losses 494 18.4.1.2 Minimizing Total Cost of Energy for Users 495 18.4.1.3 Maximizing Aggregator Profit 496 18.4.1.4 Frequency Regulation 497 18.4.1.5 Voltage regulation 497 18.4.1.6 Support for Renewable Energy Sources for Recharging of EVs 497 18.4.2 Resource Allocation for EVs Recharging in Smart Cities (Optimization Approaches) 498 18.5 Open Issues, Challenges, and Future Research Directions 498 18.5.1 Support ofWireless Power Charger 499 18.5.2 Vehicle-to-Anything 499 18.5.3 Energy Management for Smart Grid via EVs 499 18.5.4 Advance Communication Needs for Controlled EVs Recharging 499 18.5.5 EVs Control Applications 499 18.5.6 Standardization for Communication Technologies Used for EVs Recharging 500 18.6 Conclusion 500 References 500 SECTION V Security and Privacy Issues and Big Data in Smart Cities 507 19 Cyber-Security and Resiliency of Transportation and Power Systems in Smart Cities 509Seyedamirabbas Mousavian,Melike Erol-Kantarci and Hussein T. Mouftah 19.1 Introduction 509 19.2 EV Infrastructure and Smart Grid Integration 510 19.3 System Model 512 19.3.1 Model Definition and Assumptions 512 19.4 Estimating the Threat Levels in the EVSE Network 513 19.5 Response Model 514 19.6 Propagation Impacts on Power System Operations 515 19.6.1 Cyberattack Propagation in PMU Networks 515 19.6.2 Threat Level Estimation in PMU Networks 515 19.6.3 Response Model in PMU Networks 518 19.6.4 PMU Networks: Experimental Results 521 19.7 Conclusion and Open Issues 525 References 525 20 Protecting the Privacy of Electricity Consumers in the Smart City 529Binod Vaidya and Hussein T. Mouftah 20.1 Introduction 529 20.2 Privacy in the Smart Grid 530 20.2.1 Privacy Concerns over Customer Electricity Data Collected by the Utility 531 20.2.2 Privacy Concerns on Energy Usage Information Collected by a Non-Utility-OwnedMetering Device 532 20.2.3 Privacy Protection 532 20.3 Privacy Principles 532 20.4 Privacy Engineering 535 20.4.1 Privacy Protection Goals 535 20.4.2 Privacy Engineering Framework and Guidelines 538 20.5 Privacy Risk and Impact Assessment 540 20.5.1 System Privacy Risk Model 540 20.5.2 Privacy Impact Assessment (PIA) 541 20.6 Privacy Enhancing Technologies 542 20.6.1 Anonymization 544 20.6.2 Trusted Computation 545 20.6.3 Cryptographic Computation 545 20.6.4 Perturbation 546 20.6.5 Verifiable Computation 547 Acknowledgment 547 References 548 21 Privacy Preserving Power Charging Coordination Scheme in the Smart Grid 555Ahmed Sherif, Muhammad Ismail, Marbin Pazos-Revilla,Mohamed Mahmoud, Kemal Akkaya, Erchin Serpedin and Khalid Qaraqe 21.1 Introduction 555 21.1.1 Smart Grid Security Requirements 555 21.1.2 Charging Coordination Security Requirement 556 21.2 Charging Coordination and Privacy Preservation 558 21.3 Privacy-Preserving Charging Coordination Scheme 560 21.3.1 Network andThreat Models 560 21.3.2 The Proposed Scheme 561 21.3.2.1 Anonymous Data Submission 561 21.3.2.2 Charging Coordination 565 21.4 Performance Evaluation 567 21.4.1 Privacy/Security Analysis 567 21.4.2 Experimental Study 568 21.4.2.1 Setup 568 21.4.2.2 Metrics and Baselines 568 21.4.2.3 Simulation Results 569 21.5 Summary 572 Acknowledgment 573 References 573 22 Securing Smart Cities Systems and Services: A Risk-Based Analytics-Driven Approach 577Mahmoud Gad and Ibrahim Abualhaol 22.1 Introduction to Cybersecurity for Smart Cities 577 22.2 Smart Cities Enablers 579 22.3 Smart Cities Attack Surface 580 22.3.1 Attack Domains 580 22.3.1.1 Communications 580 22.3.1.2 Software 580 22.3.1.3 Hardware 580 22.3.1.4 Social Engineering 580 22.3.1.5 Supply Chain 581 22.3.1.6 Physical Security 581 22.3.2 Attack Mechanisms 582 22.4 Securing Smart Cities: A Design Science Approach 582 22.5 NIST Cybersecurity Framework 583 22.6 Cybersecurity Fusion Center with Big Data Analytics 585 22.7 Conclusion 587 22.8 Table of Abbreviations 587 References 588 23 Spatiotemporal Big Data Analysis for Smart Grids Based on Random Matrix Theory 591Robert Qiu, Lei Chu, Xing He, Zenan Ling and Haichun Liu 23.1 Introduction 591 23.1.1 Perspective on Smart Grids 591 23.1.2 The Role of Data in the Future Power Grid 594 23.1.3 A Brief Account for RMT 595 23.2 RMT: A Practical and Powerful Big Data Analysis Tool 596 23.2.1 Modeling Grid Data using Large Dimensional Random Matrices 596 23.2.2 Asymptotic Spectrum Laws 598 23.2.3 Transforms 600 23.2.4 Convergence Rate 601 23.2.5 Free Probability 603 23.3 Applications to Smart Grids 608 23.3.1 Hypothesis Tests in Smart Grids 609 23.3.2 Data-DrivenMethods for State Evaluation 609 23.3.3 Situation Awareness based on Linear Eigenvalue Statistics 612 23.3.4 Early Event Detection Using Free Probability 621 23.4 Conclusion and Future Directions 626 References 629 Index 635

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Book SynopsisA field manual on contextualizing cyber threats, vulnerabilities, and risks to connected cars through penetration testing and risk assessment Hacking Connected Cars deconstructs the tactics, techniques, and procedures (TTPs) used to hack into connected cars and autonomous vehicles to help you identify and mitigate vulnerabilities affecting cyber-physical vehicles. Written by a veteran of risk management and penetration testing of IoT devices and connected cars, this book provides a detailed account of how to perform penetration testing, threat modeling, and risk assessments of telematics control units and infotainment systems. This book demonstrates how vulnerabilities in wireless networking, Bluetooth, and GSM can be exploited to affect confidentiality, integrity, and availability of connected cars. Passenger vehicles have experienced a massive increase in connectivity over the past five years, and the trend will only continue to grow with the expansion Table of ContentsAbout the Author v Acknowledgments vii Foreword xv Introduction xix Part I Tactics, Techniques, and Procedures 1 Chapter 1 Pre-Engagement 3 Penetration Testing Execution Standard 4 Scope Definition 6 Architecture 7 Full Disclosure 7 Release Cycles 7 IP Addresses 7 Source Code 8 Wireless Networks 8 Start and End Dates 8 Hardware Unique Serial Numbers 8 Rules of Engagement 9 Timeline 10 Testing Location 10 Work Breakdown Structure 10 Documentation Collection and Review 11 Example Documents 11 Project Management 13 Conception and Initiation 15 Definition and Planning 16 Launch or Execution 22 Performance/Monitoring 23 Project Close 24 Lab Setup 24 Required Hardware and Software 25 Laptop Setup 28 Rogue BTS Option 1: OsmocomBB 28 Rogue BTS Option 2: BladeRF + YateBTS 32 Setting Up Your WiFi Pineapple Tetra 35 Summary 36 Chapter 2 Intelligence Gathering 39 Asset Register 40 Reconnaissance 41 Passive Reconnaissance 42 Active Reconnaissance 56 Summary 59 Chapter 3 Threat Modeling 61 STRIDE Model 63 Threat Modeling Using STRIDE 65 Vast 74 Pasta 76 Stage 1: Define the Business and Security Objectives 77 Stage 2: Define the Technical Scope 78 Stage 3: Decompose the Application 79 Stage 4: Identify Threat Agents 80 Stage 5: Identify the Vulnerabilities 82 Stage 6: Enumerate the Exploits 82 Stage 7: Perform Risk and Impact Analysis 83 Summary 85 Chapter 4 Vulnerability Analysis 87 Passive and Active Analysis 88 WiFi 91 Bluetooth 100 Summary 105 Chapter 5 Exploitation 107 Creating Your Rogue BTS 108 Configuring NetworkinaPC 109 Bringing Your Rogue BTS Online 112 Hunting for the TCU 113 When You Know the MSISDN of the TCU 113 When You Know the IMSI of the TCU 114 When You Don’t Know the IMSI or MSISDN of the TCU 114 Cryptanalysis 117 Encryption Keys 118 Impersonation Attacks 123 Summary 132 Chapter 6 Post Exploitation 133 Persistent Access 133 Creating a Reverse Shell 134 Linux Systems 136 Placing the Backdoor on the System 137 Network Sniffing 137 Infrastructure Analysis 138 Examining the Network Interfaces 139 Examining the ARP Cache 139 Examining DNS 141 Examining the Routing Table 142 Identifying Services 143 Fuzzing 143 Filesystem Analysis 148 Command-Line History 148 Core Dump Files 148 Debug Log Files 149 Credentials and Certificates 149 Over-the-Air Updates 149 Summary 150 Part II Risk Management 153 Chapter 7 Risk Management 155 Frameworks 156 Establishing the Risk Management Program 158 SAE J3061 159 ISO/SAE AWI 21434 163 HEAVENS 164 Threat Modeling 166 STRIDE 168 PASTA 171 TRIKE 175 Summary 176 Chapter 8 Risk-Assessment Frameworks 179 HEAVENS 180 Determining the Threat Level 180 Determining the Impact Level 183 Determining the Security Level 186 EVITA 187 Calculating Attack Potential 189 Summary 192 Chapter 9 PKI in Automotive 193 VANET 194 On-board Units 196 Roadside Unit 196 PKI in a VANET 196 Applications in a VANET 196 VANET Attack Vectors 197 802.11p Rising 197 Frequencies and Channels 197 Cryptography 198 Public Key Infrastructure 199 V2X PKI200 IEEE US Standard 201 Certificate Security 201 Hardware Security Modules 201 Trusted Platform Modules 202 Certificate Pinning 202 PKI Implementation Failures 203 Summary 203 Chapter 10 Reporting 205 Penetration Test Report 206 Summary Page 206 Executive Summary 207 Scope 208 Methodology 209 Limitations 211 Narrative 211 Tools Used 213 Risk Rating 214 Findings 215 Remediation 217 Report Outline 217 Risk Assessment Report 218 Introduction 219 References 220 Functional Description 220 Head Unit 220 System Interface 221 Threat Model 222 Threat Analysis 223 Impact Assessment 224 Risk Assessment 224 Security Control Assessment 226 Example Risk Assessment Table 229 Summary 230 Index 233

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Book SynopsisFrom the past decade vehicular ad hoc networks got tremendous attention from the industry, academia and research community. According to US National Highway Traffic Safety Administration (NHTSA), there are more than 30 thousands fatalities caused by the vehicle accidents in the U.S. each year, which worth around $250 billion economic cost annually. Research shows that 82% of these accidents can be reduced by the successful deployment of vehicular networks, because nearly 75% percent of vehicular crashes are caused by inattentive drivers. Literally, vehicular ad hoc networks means a network forms by the vehicles. But it has been evolved to network with the infrastructure as well due to the inherent intermittent nature of vehicle-to-vehicle (V2V) connection. The high mobility of vehicles, wireless communication loss and range constraints are the main reason for this intermittent V2V connection. So, now vehicular networks means communication between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). There are billions of dollars invested to research, deployment and testing of vehicular networks. For the emerging connected and autonomous vehicle (CAV), a stable vehicular networks is the foremost requirement. It is now very much visible that CAV will be the future of Intelligent Transportation System (ITS). The book is dedicated to discuss for the techniques, applications and relevant technologies of vehicular ad hoc networks and its challenges. The first chapter discuss about the routing protocols of vehicular networks. It focuses on different position-based routing protocols and their mechanisms for the successful use of vehicular networks for different applications. The second chapter discusses on the security and privacy issues on vehicular networks. A well-known security technique called Elliptic Curve Cryptography (ECC) is discussed to secure vehicular data from various tampering attacks. The third chapter discusses on the on-demand wireless broadcasting mechanism for improving data dissemination performance in terms of data delivery ratio and response time. A network-coding based approach has been investigated for improving the overall performance of existing classical data broadcast algorithms. The fourth chapter describes how to get a dependable system in the lossy communication medium. This chapter discusses on a number of fault diagnosis techniques, their strengths and weaknesses, and it reviews their implementations in mobile wireless networks. The fifth chapter discusses the basics of Blockchain technology, applications, research challenges and opportunities in the field. Finally, chapter six discuss about the identification and mitigation of the faulty nodes in the wireless network.

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Book SynopsisThe Transportation Security Administration (TSA), within the Department of Homeland Security, screens or oversees the screening of over 650 million air passengers annually at over 450 airports nationwide, and attempts to balance its aviation security mission with the freedom of movement for people and commerce. In 2011, TSA began developing new security procedures intended to strengthen security and improve the passenger experience by shortening lines and wait times. These new procedures apply risk-based, intelligence-driven screening concepts and enhance the use of technology to determine passenger risk prior to travel. As part of its responsibilities for securing civil aviation, TSA ensures that all passengers and their accessible property are screened and prohibits individuals from carrying onto aircraft items that it determines to be a threat. TSA maintains a public list of such items, known as the Prohibited Items List (PIL), and updates it as necessary. This book examines, among other things, how TSA has developed, implemented, and used expedited screening; how TSA assesses passenger risk; and the extent to which TSA has determined the Managed Inclusion system''s effectiveness. Furthermore, the book examines on what basis TSA modifies the PIL and the extent to which TSA assessed risk when considering recent modifications to the PILl; and the extent to which TSA involved stakeholders when considering these modifications.

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Book SynopsisThis book looks at the latest advances in autonomous driving, demonstrating that a future once considered science fiction is now close at hand. Acceptance of driverless cars relies on more than just the technology that delivers it; in this book the authors consider the shift in attitudes required for social acceptance and a move towards considering cars one aspect of a wider mobility solution. In addition, a clear demand is arising from gridlocked megacities across the globe. Autonomous driving offers a solution for the high pollution levels and management of the transport infrastructure where current methods are proving insufficient in places of high population density. Having highlighted the need for driverless cars, the book concludes with an ambitious agenda to ensure the successful delivery of autonomous driving. Political requirements, including investment in a new infrastructure and a commitment to collaboration across borders factors in the ten-point plan for governments seeking to establish international leaders in the latest advances in mobility services. From ethical considerations in the programming of automated driving procedures to changes in attitudes towards car ownership and design, this title is a comprehensive look at the latest revolution in mobility.Trade ReviewHerrmann, a professor of marketing, Brenner, a professor of information management, and Stadler, the CEO of Audi, explore how driverless cars will change people’s lives, the automotive and technology industry, environmental protection, the economy, legal and regulatory conditions, and other aspects of the world. They discuss facts about human driving, trends and disruptive technology related to mobility, the history and different levels of autonomous driving, economic aspects, and development phases; the technology of autonomous driving, including digitized and connected cars and cybersecurity and data privacy; the arena of autonomous driving, including areas of current use and the stakeholders and players involved; customers and their mobility behavior and expectations, as well as use cases, whether autonomous driving can fail, and product positioning; framework conditions for autonomous driving, including protection and liability, norms and standards, and ethics and morals; the impact on vehicle design, human-machine interaction, time, cost, and safety; the impact on companies and their business models, value chains, the sharing economy, and the insurance industry; the impact on society in the areas of work and welfare, competitiveness, emerging societies, and urban development; and the actions needed by the auto industry and government to manage the transition. -- Annotation ©2018 * (protoview.com) *Table of ContentsPart 1. Evolutions and Revolutions in Mobility Part 2. Perspectives on Autonomous Driving Part 3. The Technology of Autonomous Driving Part 4. The Arena of Autonomous Driving Part 5. Customers and their Mobility Behavior Part 6. Framework Conditions for Autonomous Driving Part 7. Impact on Vehicles Part 8. Impact on Companies Part 9. Impact on Society Part 10. What needs to be done?

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Book SynopsisRapid changes are underway in mobility systems worldwide, including the introduction of shared mobility solutions, Mobility as a Service and the testing of automated vehicles. These changes are driven by the development and application of ‘smart’ technologies. Transition to these technologies present significant opportunities for countries, cities and rural areas alike, offering the tempting prospect of economic benefit whilst resolving today’s safety, congestion, and pollution problems. Yet while there is a wealth of research considering how these new technologies may impact on travel behaviour, improve safety and help the environment, there is a dearth of research exploring the key governance questions that the transition to these technologies pose in their disruption of the status quo, and changes to governance that may be required for the achievement of positive social outcomes. This book aims to step into this void and in doing so presents an agenda for future research and policy action. Bringing together a collection of internationally recognised scholars, drawing on case studies from around the world, authors critically reflect on three primary governance considerations. First, the changing role of the state both during and post-transition. Second, identifying the voices shaping the smart mobility discourse. And third, analysing the implications for the state’s capacity to steer networks and outcomes as a result of these transitions. The authors argue that at present there exists a critical window of opportunity for researchers and practitioners to shape transitions and that this opportunity must be seized upon before it is too late.Trade ReviewResearchers in transportation, city planning, architecture, and similar fields explore ways to understand the challenge of governing the transition of mobility away from automobiles. Their topics include the case of mobility as a service: a critical reflection on challenges for urban transport and mobility governance, whether smart mobility is disrupting transport governance, who benefits from smart mobility: the social construction of winners and loses in the connected bikes projects in the Netherlands, planning for disruptive transport technologies: how prepared Australian transport agencies are, and whether governance matters: an international scenarios exercise. -- Annotation ©2018 * (protoview.com) *Table of ContentsIntroduction; Greg Marsden and Louise Reardon Section One: Navigating the Role of the State Chapters 1. New Governance Challenges in the Era of ‘Smart’ Mobility; Iain Docherty 2. The Case of Mobility as a Service: A Critical Reflection on Challenges for Urban Transport and Mobility Governance; Kate Pangbourne, Dominic Stead, Milos Mladenovic and Dimitris Milakis Section Two: Whose Voices are in the Smart Mobility Debate? 3. Smart Mobility: Disrupting Transport Governance?; Robyn Dowling 4. Governing the Race to Automation; Debbie Hopkins and Tim Schwanen 5. Who benefits from smart mobility policies? The Social Construction of Winners and Losers in the Connected Bikes Projects in the Netherlands; Edgar Salas Gironés and Darja Vrščaj Section Three: State Capacity 6. Governmental Capacity and the Smart Mobility Transition; Diane Davis 7. Planning for Disruptive Transport Technologies: How Prepared Are Australian Transport Agencies?; John Stone, David Ashmore, Jan Scheurer, Crystal Legacy and Carey Curtis 8. Does Governance Matter? An International Scenarios Exercise; Greg Marsden and Louise Reardon Section Four: Conclusion 9. Conclusion: A Window of Opportunity; Louise Reardon and Greg Marsden

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Book Synopsis70 per cent of the planet is covered by water, and 90 per cent of global economic trade is transported by sea. The world's seas and oceans are big business. Based on gross marine product, the ocean can be considered the world's seventh-largest economy, with the total global value of the Blue Economy predicted to rise to $3 trillion by 2030. Grounded in detailed market research, and brought to life through over 250 meticulously researched case studies, Technology and the Blue Economy presents a compelling overview of an inspiring and innovative sector that includes offshore renewable energy, ports and harbours, shipping, maritime surveillance, cyber security, aquaculture and ocean conservation. It tackles questions like these: · With Earth observation satellites providing unprecedented levels of data about the ocean, can machine learning capabilities develop at pace to make sense of all this new information? · How can ships protect themselves when one shipping firm alone records 50,000 daily attempts to breach its cyber security systems? · With floating wind farms now pushing further out to sea to convert natural energy, what role do robots have in managing essential maintenance in these more remote environments? · When passenger ferries are already sailing themselves and self-docking in port without human intervention, are we entering an age where human error is eradicated? · With fish farming predicted to account for 62 per cent of all the seafood consumed globally by 2030, how can 3D imaging cameras and net-cleaning robots help to stop mass deaths of fish that can run into millions in a single incident? · In the age of smartphone ubiquity, how important a role might social media and citizen science play in ocean conservation? · With luxury cruise ships now marketing themselves as 'smart, connected cities', crunching passenger data in real-time, do they now provide the gold standard of customer experience within the tourist industry? · Is optical scanning technology the solution to countering slavery at sea, a real concern in the south-east Asian fishing industry? · Can satellite-enabled tracking and autonomous clean-up systems help to counter one of the greatest conservation issues of the day - the fight against ocean plastic pollution? Technology and the Blue Economy explores how innovators can develop the right business models to capitalize on growth opportunities, and analyses the critical success factors for emerging technologies.Trade Review"Revealing and insightful, this book shares inspiring examples of innovations applied across a broad spectrum of Blue Economy sectors. These ideas are real and impactful and underline the importance of technology and creativity as an enabler for sustainable environments and economic growth." * David Loosley, Chief Executive, The Institute of Marine Engineering, Science and Technology *"A fascinating guide to how technology will shape the future of the Blue Economy, this book is essential reading for those looking to understand how the smart use of our oceans can support sustainable development." * Professor Dickon Howell, Director, Howell Marine Consulting, UK *"This book presents a compelling overview of the impressive range of technology innovation underpinning progress in sectors as diverse as sustainable fisheries, ocean tourism, smart port cities, shipping and seabed mapping. Start-ups and tech developers in all sectors could learn from the up-to-the-minute case studies presented in this thoroughly researched and well written book." * Tony Hughes, Dealmaker, Global Entrepreneur Programme – the UK’s Department for International Trade *"Here, at last, is a book that sets out the scale of challenges and opportunities that our oceans present, by three authors bringing enormous knowledge to the domain. The Blue Economy is so much more diverse than the traditional marine and maritime sectors, and this book is a must-read for anyone interested to understand where the Blue Economy is heading." * Dr. Jonathan Williams, CEO, Marine South East, UK *"The breadth of innovation across the blue economy is extraordinary. Andy, Nick and Jonathan have explored, sector by sector, to reveal insights and applications that are revolutionising industries and opening doors for new commercial opportunities in the seas and oceans." * Aidan Thorn, Maritime Innovation Expert *Table of Contents Chapter - 01: An introduction to the blue economy; Chapter - 02: Shipping; Chapter - 03: Ports and harbours; Chapter - 04: Offshore renewables; Chapter - 05: The cruise industry; Chapter - 06: Maritime surveillance; Chapter - 07: Aquaculture; Chapter - 08: Hydrography and bathymetry; Chapter - 09: Ocean observation; Chapter - 10: Sustainable fisheries; Chapter - 11: Subsea monitoring; Chapter - 12: Safety of life at sea; Chapter - 13: Conclusion

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Book SynopsisInventing Mobility For All: Mastering Mobility-as-a-Service with Self-Driving Vehicles explores ‘Mobility-as-a-Service’ and explains the impact of this mobility concept on social and societal life, as well as on global travel behaviours. In this volume, Andreas Herrmann and Johann Jungwirth powerfully illustrate that mobility is a fundamental human right that can best be fulfilled with new autonomous vehicle development and use, showcasing how these forms of mobility will improve accessibility for the disabled, aid protection for the environment and to open how we design our cities in completely new ways.Trade ReviewMobility-as-a-Service can make a decisive contribution to improving the traffic situation in many megacities. MaaS concepts are already being tested in numerous Chinese cities. We are on the threshold of implementation. This book vividly illustrates the idea, concepts and implications around Mobility-as-a-Service, making an important contribution to better mobility - for cities, for people, for the environment. -- Prof. Dr. Zheng Han, Chair of Innovation and Entrepreneurship, Sino-German School for Postgraduate Studies (CDHK), School of Economics and Management, Tongji University, Shanghai.Mobility-as-a-Service is an opportunity to completely rethink our cities. Roads and parking lots can be repurposed or deconstructed and used for living spaces, playgrounds or denser mixed-use development and affordable housing. This book describes numerous approaches so that in the future we build our cities around people and not cars. -- Gabe Klein, Founding Partner of Cityfi, Venture Partner at Fontinalis Partners, and former Commissioner of the Chicago and Washington DC Departments of Transportation.Table of ContentsPart 1: Mobility, Prosperity and the Environment Chapter 1. Can We Still Go Places? Chapter 2. Mobility Means Prosperity Chapter 3. Social Costs of Mobility Chapter 4. All Just a Misunderstanding? Part 2: Into the Cities Chapter 5. The Rush to the Cities Chapter 6. More and More Traffic Chapter 7. The Cities Fight Back Chapter 8. What Is Happening in Rural Areas? Part 3: Radical Change in the Auto Industry Chapter 9. A Disintegrating Supply Chain Chapter 10. Autonomous, Electric and Connected Chapter 11. All Together Now Part 4 - Outlook for Mobility-as-a-Service Chapter 12. Making Mobility Better Chapter 13. Nothing Works Without Apps Chapter 14. Reinventing the Value Chain Chapter 15. Multimodal Transportation Chapter 16. Pods and Shuttles Chapter 17. But Will It Be Profitable? Chapter 18. A Wager on the Future? Part 5 - What Customers Want Chapter 19. If Wishes Were Horses Chapter 20. Going Places, But Differently Part 6 - What Companies Can Do (And Need To) Chapter 21. What Matters Chapter 22. Wanted: A Business Model Part 7 - Cities Lead the Way Chapter 23. Ideas, Projects & Visions Chapter 24. There Is Another Way Part 8 - What Are the Benefits of Mobility-as-a-Service? Chapter 25. Jobs and Prosperity Chapter 26. More Life, Less Traffic Chapter 27. Mobility For All Chapter 28. New Locations, New Nations Part 9 - What Will It Take to Make It Work?

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Book SynopsisWith AI advancements eliciting imminent changes to our transport systems, this enlightening Handbook presents essential research on this evolution of the transportation sector. It focuses on not only urban planning, but relevant themes in law and ethics to form a unified resource on the practicality of AI use.The Handbook on Artificial Intelligence and Transport provides a full investigation of the most recent AI transport developments, authored by an international collective of renowned contributors. Chapters examine several often challenging topics such as autonomous driving and cyber security ethics. They conclude that AI technology is likely to offer resolutions to persistent transport issues that have been almost impossible to solve using conventional approaches.This timely Handbook will be an important resource for students of transport planning and engineering, innovation and regional law. It will also benefit practitioners within the sectors of urban planning and engineering seeking updated evidence on the role of AI in transport improvement.Trade Review‘Under the astute editorship of Hussein Dia, the Handbook on Artificial Intelligence and Transport deftly elucidates a panoply of AI advancements across a myriad of transportation spheres. An indispensable tome for both academia and industry, it propels the transportation field towards a future replete with innovation and sagacity.’ -- Der-Horng Lee, Zhejiang University-University of Illinois Urbana-Champaign InstituteTable of ContentsContents: Introduction to the Handbook on Artificial Intelligence and Transport 1 Hussein Dia PART I SHORT-TERM TRAFFIC FORECASTING AND CONGESTION PREDICTION 1 A comparative evaluation of established and contemporary deep learning traffic prediction methods 14 Ta Jiun Ting, Scott Sanner, and Baher Abdulhai 2 Fault tolerance and transferability of short-term traffic forecasting hybrid AI models 47 Rusul Abduljabbar, Hussein Dia, and Pei-Wei Tsai 3 A review of deep learning-based approaches and use cases for traffic prediction 80 Rezaur Rahman, Jiechao Zhang, and Samiul Hasan 4 The ensemble learning process for short-term prediction of traffic state on rural roads 102 Arash Rasaizadi, Fateme Hafizi, and Seyedehsan Seyedabrishami 5 Using machine learning and deep learning for traffic congestion prediction: a review 124 Adriana-Simona Mihaita, Zhulin Li, Harshpreet Singh, Nabin Sharma, Mao Tuo, and Yuming Ou PART II PUBLIC TRANSPORT PLANNING AND OPERATIONS 6 The potential of explainable deep learning for public transport planning 155 Wenzhe Sun, Jan-Dirk Schmöcker, Youxi Lai, and Koji Fukuda 7 Neural network approaches for forecasting short-term on-road public transport passenger demands 176 Sohani Liyanage, Hussein Dia, Rusul Abduljabbar, and Pei-Wei Tsai PART III RAILWAYS 8 Artificial intelligence in railway traffic planning and management Taxonomy, a systematic review of the state-of-the-art of AI, and transferability analysis 222 Ruifan Tang, Zhiyuan Lin, Ronghui Liu, Rob M.P. Goverde, and Nikola Bešinović 9 Artificial intelligence in railways: current applications, challenges, and ongoing research 249 Lorenzo De Donato, Ruifan Tang, Nikola Bes̆inović, Francesco Flammini, Rob M.P. Goverde, Zhiyuan Lin, Ronghui Liu, Stefano Marrone, Elena Napoletano, Roberto Nardone, Stefania Santini, Valeria Vittorini PART IV FREIGHT AND AVIATION 10 Artificial intelligence and machine learning applications in freight transport 285 Yijie Su, Hadi Ghaderi, and Hussein Dia 11 A paradigm shift in the aviation industry with digital twin, blockchain, and AI technologies 323 Tommy Cheung, Bo Li, and Zheng Lei PART V VIDEO ANALYTICS AND MACHINE VISION APPLICATIONS 12 A deep learning approach to real-time video analytics for people and passenger counting 348 Chris McCarthy, Hadi Ghaderi, Prem Prakash Jayaraman, and Hussein Dia 13 AI machine vision for safety and mobility: an autonomous vehicle perspective 380 Sagar Dasgupta, Xishi Zhu, Muhammad Sami Irfan, Mizanur Rahman, Jiaqi Gong, and Steven Jones PART VI DATA ANALYTICS AND PATTERN ANALYSIS 14 A review of AI-enabled and model-based methodologies for travel demand estimation in urban transport networks 411 Sajjad Shafiei and Hussein Dia 15 Recombination-based two-stage out-of-distribution detection method for traffic flow pattern analysis 434 Yuchen Lu, Ying Jin, and Xi Chen 16 An intelligent machine learning alerting system for distracted pedestrians 465 M.L. Cummings, Lixiao Huang, and Michael Clamann PART VII PREDICTIVE TRAFFIC SIGNAL CONTROL 17 A critical review of traffic signal control and a novel unified view of reinforcement learning and model predictive control approaches for adaptive traffic signal control 482 Xiaoyu Wang, Baher Abdulhai, and Scott Sanner PART VIII AI ETHICS AND CYBERSECURITY CHALLENGES 18 A review of AI ethical and moral considerations in road transport and vehicle automation 534 Dorsa Alipour and Hussein Dia 19 Cybersecurity challenges in AI-enabled smart transportation systems 567 Lyuyi Zhu, Ao Qu, and Wei Ma 20 Autonomous driving: present and emerging trends of technology, ethics, and law 596 Gustav Lindberg, Ikeya Carrero, Fermín Mallor, Julián Estévez, Manuela Battaglini, and Ricardo Vinuesa Index 617

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Book SynopsisSmart roads are road infrastructures with integrated structural materials, sensors, information centres, and energy systems. They are intended to extend the road's service life and performance, reduce safety risks, and improve service quality. Several smart road pilot projects have been initiated, such as precast pavements with integrated optical fibres, self-healing asphalt material, self-snow-melting systems and solar pavements. Smart roads are likely to play an important role in future sustainable transport systems and supplying data for intelligent transportation systems (ITS). This book brings together the latest research into technologies for novel and smart road infrastructures. Coverage includes road surface technologies, techniques for road-based energy harvesting, sustainable pavement approaches, informatization of the road, and use of the data gained for various cloud-based services including ITS. A systematic guide to an emerging topic, this book is aimed particularly at researchers in academia and industry, including those working for ITS providers and organizations. It will also be of use to practitioners in ITS organizations and governmental transport agencies.Table of Contents Chapter 1: Smart road: concept and architecture Chapter 2: Pavement technology for autonomous driving Chapter 3: Prefabricated smart pavement Chapter 4: Real-time accurate positioning technology in intelligent transportation scenes Chapter 5: “Smart Site” dynamic monitoring system of highway engineering quality Chapter 6: Smart road in China Chapter 7: Analysis of resonant rubblizing technology and its energy absorption mechanism

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Book SynopsisIntelligent Transportation Systems (ITS) are expected to add considerable productivity to existing transportation infrastructure and to therefore partially reduce the need for more physical infrastructure such as additional lanes of roadway. But there are huge barriers to achieving this vision ranging from the technical to the institutional. In this book a new outcome oriented methodology is developed and applied to a diverse set of ITS case studies in an effort to gain insight into the barriers to deployment. The case studies, most from the National Capital Region (Washington) in the US, include but are not limited to evaluation of electronic tolling, truck roll over warning systems, Advanced Traffic Information Systems (ATIS), variable message signs (VMS), ITS enhanced emergency management systems and ITS bridge operations. The evaluation methodology bears similarity to the benefit/cost balance sheet approach. Full cost (benefit) assessment is adopted with multiple externalities (environment, economic development, social equity issues, etc.) formally included in each of the individual evaluations. Transportation policymakers as well as scholars and students of economic, public policy and political science will find this study useful and informative.Trade Review'The macro-focus makes the book a nice complement to already existing texts on more disaggregate issues. I believe the book offers a wealth of information on ITS applications operating in the DC region. It thus offers stimulating reading for those involved in the design, evaluation and research of ITS applications and other types of transport policy projects.' -- Erik T. Verhoef, The Economic JournalTable of ContentsContents: 1. Introduction Part I: A Multi-criteria ITS Evaluation Methodology and Applications 2. Methodological and Technical Challenges in Regional Evaluation of ITS: Induced and Direct Effects 3. Electronic Toll Collection (ETC) in the Dulles Corridor 4. The Variable Message Sign System of Northern Virginia 5. Automatic Truck Rollover Warning System 6. The Montgomery County Advanced Transportation Management System Part II: Applications of Alternative Methodologies to ITS 7. Smart Flexible Integrated Real-time Enhanced System (SaFIRES) 8. The Woodrow Wilson Bridge 9. Incident Management and Intelligent Transportation Systems Technology: Estimating Benefits for Northern Virginia Index

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Book SynopsisThe use and management of multimodal transport systems, including car-pooling and goods transportation, have become extremely complex, due to their large size (sometimes several thousand variables), the nature of their dynamic relationships as well as the many constraints to which they are subjected. The managers of these systems must ensure that the system works as efficiently as possible by managing the various causes of malfunction of the transport system (vehicle breakdowns, road obstructions, accidents, etc.). The detection and resolution of conflicts, which are particularly complex and must be dealt with in real time, are currently processed manually by operators. However, the experience and abilities of these operators are no longer sufficient when faced with the complexity of the problems to be solved. It is thus necessary to provide them with an interactive tool to help with the management of disturbances, enabling them to identify the different disturbances, to characterize and prioritize these disturbances, to process them by taking into account their specifics and to evaluate the impact of the decisions in real time. Each chapter of this book can be broken down into an approach for solving a transport problem in 3 stages, i.e. modeling the problem, creating optimization algorithms and validating the solutions. The management of a transport system calls for knowledge of a variety of theories (problem modeling tools, multi-objective problem classification, optimization algorithms, etc.). The different constraints increase its complexity drastically and thus require a model that represents as far as possible all the components of a problem in order to better identify it and propose corresponding solutions. These solutions are then evaluated according to the criteria of the transport providers as well as those of the city transport authorities. This book consists of a state of the art on innovative transport systems as well as the possibility of coordinating with the current public transport system and the authors clearly illustrate this coordination within the framework of an intelligent transport system. Contents 1. Dynamic Car-pooling, Slim Hammadi and Nawel Zangar. 2. Simulation of Urban Transport Systems, Christian Tahon, Thérèse Bonte and Alain Gibaud. 3. Real-time Fleet Management: Typology and Methods, Frédéric Semet and Gilles Goncalves. 4. Solving the Problem of Dynamic Routes by Particle Swarm, Mostefa Redouane Khouahjia, Laetitia Jourdan and El Ghazali Talbi. 5. Optimization of Traffic at a Railway Junction: Scheduling Approaches Based on Timed Petri Nets, Thomas Bourdeaud’huy and Benoît Trouillet. About the Authors Slim Hammadi is Full Professor at the Ecole Centrale de Lille in France, and Director of the LAGIS Team on Optimization of Logistic systems. He is an IEEE Senior Member and specializes in distributed optimization, multi-agent systems, supply chain management and metaheuristics. Mekki Ksouri is Professor and Head of the Systems Analysis, Conception and Control Laboratory at Tunis El Manar University, National Engineering School of Tunis (ENIT) in Tunisia. He is an IEEE Senior Member and specializes in control systems, nonlinear systems, adaptive control and optimization. The multimodal transport network customers need to be oriented during their travels. A multimodal information system (MIS) can provide customers with a travel support tool, allowing them to express their demands and providing them with the appropriate responses in order to improve their travel conditions. This book develops methodologies in order to realize a MIS tool capable of ensuring the availability of permanent multimodal information for customers before and while traveling, considering passengers mobility.Table of ContentsPreface xi Slim HAMMADI and Mekki KSOURI Chapter 1. Dynamic Car-pooling 1 Slim HAMMADI and Nawel ZANGAR 1.1. Introduction 1 1.2. State of the art 2 1.3. Complexity of the optimized dynamic car-pooling problem: comparison and similarities with other existing systems 8 1.3.1. Graphical modeling for the implementation of a distributed physical architecture 9 1.3.2. Collection of requests for car-pooling and data modeling 11 1.3.3. Matrix structure to collect information on requests 14 1.3.4. Matrix representation for modeling car-pooling offers 17 1.3.5. Modeling constraints of vehicles’ allocation to users 21 1.3.6. Geographical network subdivision served and implementation of a physical distributed dynamic architecture 26 1.4. ODCCA: an optimized dynamic car-pooling platform based on communicating agents 33 1.4.1. Multi-agent concept for a distributed car-pooling system 33 1.5. Formal modeling: for an optimized and efficient allocation method 40 1.5.1. D3A: Dijkstra Dynamic Distributed Algorithm 40 1.5.2. ODAVe: Optimized Distributed Allocation of Vehicle to users 44 1.6. Implementation and deployment of a dynamic car-pooling service 47 1.6.1. Deployment of ODCCA: choosing a hybrid architecture 49 1.6.2. Layered architecture 51 1.6.3. Testing and implementation scenario 55 1.7. Conclusion 65 1.8. Bibliography 66 Chapter 2. Simulation of Urban Transport Systems 71 Christian TAHON, Thérèse BONTE and Alain GIBAUD 2.1. Introduction 71 2.2. Context 72 2.3. Simulation of urban transport systems 75 2.3.1. Non-guided transport systems 76 2.3.2. Guided transport systems 77 2.4. The types of modeling 80 2.4.1. Nature of the models 80 2.4.2. Macrosimulation, mesoscopic simulation, micro simulation 81 2.5. Modeling approaches 83 2.6. Fields of application 83 2.7. Software tools 86 2.8. Simulation of the Valenciennes transport network with QUEST software 87 2.8.1. Problem 87 2.8.2. Network operation in normal mode 87 2.8.3. Disturbed mode network function 90 2.9. The QUEST software 92 2.9.1. Presentation 92 2.9.2. Modeling 92 2.10. Network modeling in normal mode 94 2.10.1. Topology of traffic networks 94 2.10.2. Bus lines 95 2.10.3. Vehicles 96 2.10.4. Modeling 96 2.10.5. Stops 97 2.10.6. Passengers 101 2.10.7. The flow of connecting passengers 102 2.11. Network modeling in degraded mode 103 2.11.1. Disturbances 103 2.11.2. Regulatory procedures 105 2.12. Simulation results 107 2.13. Conclusion/perspectives 107 2.14. Self-organization of traffic – the FORESEE simulator 108 2.14.1. General problem 108 2.14.2. FORESEE simulator 113 2.14.3. Results 117 2.15. Conclusion – perspectives 124 2.15.1. Sustainability of the information 125 2.15.2. Information aggregation algorithms 125 2.15.3. Cooperation efficiency 125 2.15.4. Deployment of the proposed approach 126 2.16. Bibliography 127 Chapter 3.Real-time Fleet Management: Typology and Methods 139 Frédéric SEMET and Gilles GONCALVES 3.1. Introduction 139 3.2. General context of RTFMP 140 3.2.1. RTFMP characteristics 140 3.2.2. Application field of RTFMPs 142 3.3. Simulation platform for real-time fleet management 144 3.3.1. Dynamic management of vehicle routing 144 3.3.2. Routing management under time window constraints 146 3.3.3. General architecture of the simulation platform 147 3.3.4. Consideration of uncertainties on requests 151 3.3.5. Consideration of information linked to traffic 156 3.4. Real-time fleet management: a case study 162 3.4.1. General architecture of the optimization engine 163 3.4.2. Itinerary calculation and length estimation 164 3.4.3. The static route planning problem 165 3.4.4. Route planning and modification of the transport plan 166 3.5. Conclusion 168 3.6. Bibliography 168 Chapter 4. Solving the Problem of Dynamic Routes by Particle Swarm 173 Mostefa Redouane KHOUAHJIA, Laetitia JOURDAN and El Ghazali TALBI 4.1. Introduction 173 4.2. Vehicle routing problems 174 4.2.1. The static vehicle routing problem 174 4.2.2. The dynamic vehicle routing problem (DVRP) 176 4.2.3. Importance of dynamic routing problems 178 4.3. Resolution scheme of the dynamic vehicle routing problem 179 4.3.1. Event planner 179 4.3.2. Particle swarm optimization 181 4.4. Adaptation of the PSO metaheuristic for the dynamic vehicle routing problem 184 4.4.1. Representation of particles 184 4.4.2. Velocity and movement of particles 185 4.4.3. The APSO algorithm (Adaptive Particle Swarm Optimization) 187 4.4.4. Adaptive memory mechanism 188 4.5. Experimental results 189 4.5.1. Datasets 189 4.5.2. Experiments and analysis 190 4.5.3. Measure of dynamicity 192 4.6. Conclusion 196 4.7. Bibliography 196 Chapter 5. Optimization of Traffic at a Railway Junction: Scheduling Approaches Based on Timed Petri Nets 199 Thomas BOURDEAUD’HUY and Benoît TROUILLET 5.1. Introduction 199 5.2. Scheduling in a railway junction 201 5.2.1. Classical scheduling 201 5.2.2. Flexible system scheduling 202 5.2.3. Dual Gantt diagram 203 5.2.4. The railway junction saturation problem 204 5.3. Petri nets for scheduling 206 5.3.1. Place/Transition Petri net 206 5.3.2. T-timed Petri nets 209 5.3.3. Controlled executions 211 5.3.4. Reachability problems in TPNs 212 5.3.5. Modeling of a railway junction with Petri nets 213 5.3.6. Approaches to solving the timed reachability problem 214 5.4. Incremental model for TPNs 216 5.4.1. Formulation operators “+” and “s” 220 5.4.2. Integer Mathematical Models 223 5.4.3. Numerical experiments 225 5.4.4. Study of the illustrative example of Figure 5.5 227 5.4.5. Conclusion and future work 228 5.5. A (max,+) approach to scheduling 229 5.5.1. Introduction and production hypotheses 230 5.5.2. Construction of a simple event graph associated with the initial model 233 5.5.3. Resolution of resource sharing 236 5.5.4. Application 242 5.5.5. Overview 246 5.6. Conclusion 247 5.7. Bibliography 248 List of Authors 253 Index 255

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Book SynopsisThis book studies the simulation of wireless networking in the domain of Intelligent Transportation Systems (ITS) involving aircraft, railway and vehicular communication. On this subject, particular focus is placed on effective communication channels, mobility modeling, multi-technology simulation and global ITS simulation frameworks. Networking Simulation for Intelligent Transportation Systems addresses the mixing of IEEE802.11p and LTE into a dedicated simulation environment as well as the links between ITS and IoT; aeronautical mobility and VHD Data Link (VDL) simulation; virtual co-simulation for railway communication and control-command; realistic channel simulation, mobility modeling and autonomic simulation for VANET and quality metrics for VANET. The authors intend for this book to be as useful as possible to the reader as they provide examples of methods and tools for running realistic and reliable simulations in the domain of communications for ITS.Table of ContentsPreface xi Chapter 1 Simulation of Convergent Networks for Intelligent Transport Systems with VSimRTI 1 Robert PROTZMANN, Björn SCHÜNEMANN and Ilja RADUSCH 1.1 Introduction 1 1.2 Fundamentals of cooperative ITS 2 1.2.1 Message types 2 1.2.2 Application categories 3 1.2.3 Supporting facilities 4 1.3 Overall simulation framework 5 1.4 Simulation of cellular networks 6 1.4.1 Regions and cells 10 1.4.2 Delay models 11 1.4.3 PR-Model and PL-Model 12 1.4.4 Capacity Model 13 1.4.5 Topological and geographical messaging 14 1.5 Simulation study 14 1.5.1 Evaluation metrics 16 1.5.2 Simulation set-up 18 1.5.3 Simulation results 21 1.6 Conclusion 25 1.7 Bibliography 26 Chapter 2 Near-field Wireless Communications and their Role in Next Generation Transport Infrastructures: an Overview of Modelling Techniques 29 Christian PINEDO, Marina AGUADO, Lara RODRIGUEZ, Iñigo ADIN, Jaizki MENDIZABAL and Guillermo BISTUÉ 2.1 Near-field wireless technologies 30 2.1.1 Near-field versus far-field 30 2.1.2 Near-field-based technologies in transport 33 2.2 Characterization of near-field communications 36 2.2.1 Electrical models 37 2.2.2 Analysis of the mutual inductance of a squared inductive coupling 37 2.2.3 Computer-aided electromagnetic calculation 40 2.3 Discrete event simulators 42 2.3.1 Riverbed Modeler 43 2.3.2 OMNeT++ 44 2.3.3 ns-2 45 2.3.4 ns-3 45 2.3.5 Discrete event simulator comparison for near-field communication 46 2.4 Conclusions 47 2.5 Bibliography 48 Chapter 3 Trace Extraction for Mobility in Civil Aeronautical Communication Networks Simulation 51 Fabien GARCIA and Mickaël ROYER 3.1 Traffic regulations 52 3.1.1 General airspace 52 3.1.2 North Atlantic airspace 53 3.2 Mobility for network simulation 54 3.2.1 Types of mobility models for AANETs 54 3.2.2 Comparison of mobility model types 55 3.3 Example of mobility trace extraction 56 3.3.1 Extraction of information 57 3.3.2 Traces filtering 57 3.3.3 Enhancing traces 58 3.4 Toward cooperative trajectories 60 3.5 Bibliography 60 Chapter 4 Air-Ground Data Link Communications in Air Transport 61 Christophe GUERBER, Alain PIROVANO and José RADZIK 4.1 Introduction 61 4.1.1 Context 61 4.1.2 OMNeT++ 63 4.2 Continental air-ground data link communications and VDL mode 2 63 4.2.1 Communication system 63 4.2.2 Dimensioning parameters and bottlenecks 65 4.2.3 Simulation model 67 4.2.4 Analysis of simulation results 69 4.3 Oceanic air-ground data link communications and AMS(R)S 71 4.3.1 The aeronautical mobile satellite (route) service and Classic Aero 71 4.3.2 Dimensioning parameters and bottlenecks 73 4.3.3 Simulation model 74 4.3.4 Analysis of simulation results 75 4.4 Summary and further work 76 4.5 Bibliography 77 Chapter 5 A Virtual Laboratory as an Assessment Tool for Wireless Technologies in Railway Systems 79 Patrick SONDI, Eric RAMAT and Marion BERBINEAU 5.1 Introduction 80 5.2 ERTMS subsystems and related test beds 81 5.2.1 The functional subsystem of the ERTMS 81 5.2.2 The telecommunication subsystem of the ERTMS 84 5.3 A virtual laboratory based on co-simulation for ERTMS evaluation 86 5.3.1 Why a co-simulation approach? 86 5.3.2 Which data and processes must be modeled in each simulator? 87 5.3.3 Overall architecture of the ERTMS–OPNET virtual laboratory 89 5.3.4 Synchronization modes 90 5.3.5 Virtual laboratory implementations in the ERTMS simulator 92 5.3.6 Virtual laboratory implementations in OPNET 93 5.3.7 Virtual laboratory implementations in the co-simulation manager 95 5.4 Effective use of the ERTMS–OPNET virtual laboratory 97 5.4.1 A co-simulation scenario with the ERTMS–OPNET virtual laboratory 97 5.4.2 Efficiency of the co-simulation approach in the evaluation of railway systems 101 5.5 Conclusion 104 5.6 Bibliography 105 Chapter 6 Emulating a Realistic VANET Channel in Ns-3 107 Hervé BOEGLEN, Benoit HILT and Frédéric DROUHIN 6.1 Introduction 107 6.2 Influence of the channel propagation model on VANET simulation 107 6.2.1 A realistic IEEE802.11 PHY layer 108 6.2.2 Accurate VANET channel propagation modeling 109 6.3 A way to realistic channel modeling with ns-2 112 6.4 Realistic channel modeling with ns-3 114 6.4.1 The Yans WiFi model 114 6.4.2 The Physim Wi-Fi model emulating OFDM-based transmission 115 6.4.3 Data transmission at ns-3 PHY level 116 6.4.4 The internals of WiFi channel modeling 117 6.5 Case studies: emulation of realistic VANET channel models in ns-3 117 6.5.1 A simplified VANET channel model for an urban environment 118 6.5.2 A normalized VANET channel model for urban environments 121 6.6 Conclusion and discussion 123 6.7 Appendix A: The Abbas et al Model Implementation 125 6.8 Bibliography 130 Chapter 7 CONVAS: Connected Vehicle Assessment System for Realistic Co-simulation of Traffic and Communications 133 Justinian ROSCA, Ines UGALDE, Praprut SONGCHITRUKSA and Srinivasa SUNKARI 7.1 Introduction 133 7.2 Related work 135 7.3 CONVAS co-simulation platform 138 7.4 Realistic DSRC channel models 139 7.4.1 CONVAS propagation models 141 7.4.2 Model tuning based on real-world data 142 7.5 Channel model tuning 143 7.5.1 Michigan safety pilot model deployment data 143 7.5.2 Estimation of PDR 144 7.5.3 Model tuning 146 7.6 Connected vehicle applications 149 7.6.1 Intelligent dilemma zone avoidance 149 7.6.2 IDZA implementation in CONVAS 150 7.6.3 IDZA performance criteria 151 7.7 Experimental results 151 7.7.1 CONVAS setup 151 7.7.2 Co-simulation results 152 7.8 Conclusions 159 7.9 Acknowledgments 160 7.10 Bibliography 161 Chapter 8 Highway Road Traffic Modeling for ITS Simulation 165 Marco GRAMAGLIA, Marco FIORE, Maria CALDERON, Oscar TRULLOLS-CRUCES and Diala NABOULSI 8.1 Introduction 165 8.2 Road traffic models 166 8.2.1 Traffic input feeds 168 8.2.2 Mobility models 169 8.3 Fine-tuned measurement-based model 170 8.4 Comparative analysis of road traffic models 174 8.4.1 Case study scenarios 174 8.4.2 Connectivity metrics 175 8.4.3 Results 176 8.5 Fundamental properties of highway vehicular networks 178 8.6 Discussion and conclusions 181 8.7 Bibliography 182 Chapter 9 F-ETX: A Metric Designed for Vehicular Networks 185 Sébastien BINDEL, Benoit HILT and Serge CHAUMETTE 9.1 Introduction 185 9.2 Link quality estimators 187 9.2.1 Hardware-based LQE 188 9.2.2 Software-based 189 9.2.3 Discussion 190 9.3 Analysis of legacy estimation techniques 190 9.3.1 Type of window 191 9.3.2 Window analysis 193 9.4 The F-ETX metric 195 9.4.1 Window management algorithms 195 9.4.2 Multi-assessment approach 197 9.4.3 Routing integration framework 199 9.5 Simulation settings 201 9.5.1 First scenario 202 9.5.2 Second scenario 202 9.6 Simulation results 202 9.6.1 Performance of the multi-estimators 203 9.6.2 Performance of routing protocols 206 9.7 Conclusion 208 9.8 Bibliography 209 Chapter 10 Autonomic Computing and VANETs: Simulation of a QoS-based Communication Model 211 Nader MBAREK, Wahabou ABDOU and Benoît DARTIES 10.1 Introduction 211 10.2 Autonomic Computing within VANETs 212 10.2.1 Autonomic Computing 212 10.2.2 Autonomic vehicular communications 213 10.3 Broadcasting protocols for VANETs 213 10.3.1 Deterministic methods 215 10.3.2 Stochastic methods 216 10.4 Autonomic broadcasting within VANETs 218 10.4.1 Optimization of broadcasting protocols in VANETs 218 10.4.2 Self-management architecture 219 10.4.3 QoS-based broadcasting 221 10.5 Simulation of a QoS-based communication model 222 10.5.1 ADM: autonomic dissemination method 222 10.5.2 Simulation environment 228 10.5.3 Performance evaluation 229 10.6 Conclusion 231 10.7 Bibliography 232 List of Authors 235 Index 239

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Book SynopsisSmart cities are cities which use different types of electronic methods and sensors to collect data. The gathered information and data is then used to manage assets, resources and services efficiently to improve the operations across the city. This book provides a new insight for the current issues and opportunities in smart cities and related concepts in the next generation of urban evolution. The smart cities of tomorrow engage locals, visitors, governments and businesses in the intelligent, collaborative and connected ecosystem. To this end, the goal of this book is to provide better understanding of city services but also enhancing and evaluating the local and visitor experience and city decision-making processes by creating livable environments and business solutions. With international contributions from well-respected and international academics, it brings state-of-art knowledge on marketing management (and related areas e.g., urban studies) from a new modern perspective within the smart cities. Via academic research and international case studies, it discusses issues such as: • Smart tourists in smart cities • The evolution of the smart city • Smart trends in the tourism and hospitality industry • Smart sports in smart cities • Creating a smart tourist destinations • What does it mean for the locals – the smart city as a proposal to improve the quality of life of residentsTable of ContentsCh 1 The Evolution Process of Smart Tourism Initiatives (Abbie-Gayle Johnson, Jillian M. Rickly and Scott McCabe); Ch 2 Smart tourists in smart cities (Tomáš Gajdošík); Ch 3 Advances in Smart Destination Management and Public Governance:Tourism Innovation ecosystems for Digital; Ch 4 Smart Destinations: A Multiple Case study of European Smartest and Most Visited Cities (Kadir Çakar); Ch 5 Modes of destination metagovernance and smart governance in Milan: A longitudinal perspective (Alberto Amore et al); Ch 6 Smart Stem Education for active ageing (Anthony Kong et al); Ch 7 Smart cities digital transformation (Ekaterina Glebova, Wojciech Lewicki); Ch 8 Smart Sports in Smart Cities (Ekaterina Glebova, Michel Desbordes); Ch 9 Madeira Island – Re-thinking the development of the tourism sector (Luiz Pinto Machado and Antonio Almeida); Ch 10 Co-Creating and Co-Destructing Personalised Experiences through Smart Destination Infrastructure (Katerina Volchek, Dimitrios Buhalis and Rob Law); Ch 11 Is Smart Technology an Opportunity or a Challenge for Restaurant Employees?: Perception towards Smart ICTs and its Antecedents (Yakup Kemal Özekİcİ and Cemal Ersin Sİlİk); Ch 12 Reconnoitering the Role of Human Capital in the Development of Smart Cities: A Systematic Review (Dr. Aruditya Jasrotia); Ch 13 Co-creation of smart value on smart ecosystems – past trends and future directions in tourism literature (Estrella Diaz, Águeda Esteban, Christina Koutra and Sofia Almeida); Ch 14 Smart trends in the tourism and hospitality industry (Evrim Celtek); Ch 15 From Smart City 1.0 to Smart City 3.0: Deep Understanding of the Smart City Concept and Evolution (Diogo Correia and Leonor Teixeira); Ch 16 Smart City as a Proposal to Improve the Quality of Life of Residents and Promote a Smart Tourist Destination: the Case of Barranco, Lima, Peru (Otto Regalado-Pezua et al); Ch 17 The Viable System Model as an instrument to manage the creation of value in smart (Susana Romero Juarez et al); Ch 18 The French-style Smart Cities (Cyril Blanchet et al); Index

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Book SynopsisThis book introduces readers to the key provisions of the URRAN-based technical asset management system - a methodology for managing resources and risks by analyzing and ensuring the required levels of reliability and safety in Russia’s railway transport facilities. It describes the architecture of the URRAN information system’s unified corporate platform (UCP URRAN) and its subsystems for infrastructure facilities and rolling stock complexes. It also highlights the UCP URRAN’s prospects for development, especially in the application of artificial intelligence to predict dangerous events in railway transport operation. The book is chiefly intended for specialists engaged in practical work on the technical maintenance of railway transport facilities. It can also be used as a reference guide for students and researchers at railway universities or professionals who are dealing with problems in technical asset management in other industries.Table of Contents1. Introduction.- 2. Problems of Managing Technical Assets in Railway Domain.- 3. Conceptual Provisions for Integrated Risk-Based Management of Reliability, Safety, and Resources.- 4. Basic Concepts and Indicators of Dependability and Functional Safety of Railway Transport Facilities.- 5. Standardization of the Facilities of Railway Transport and the Normalization of Dependability Indicators.- 6. Fundamentals of Management of Technical and Industrial Risks on Railway Transport.- 7. Resource Management of Railway Transport Facilities.- 8. Assessment of the Activities of Structural Divisions of Railway Transport.- 9. Unified Corporate Platform URRAN (UCP URRAN).- 10. Conclusion.

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Book SynopsisThis book contains an abundance of numerical analyses based on significant data sets, illustrating the close affiliation between transport systems development and quality of life. How to ensure accessibility standards for public transport for people with special needs? Which multi-criteria methods can support the problem of vehicle selection in freight transport, and which ones should be taken into account in the case of problems related to regional rail transport? What kind of How to assess technical condition of transport means? What factors should be taken into account when assessing the quality of passenger service? How to include zero emission vehicles in the consideration of transport plans? This book provides you with answers to these and many other questions. With regard to the research results discussed and the selected solutions applied, the book primarily addresses the needs of three target groups: Scientists and researchers (ITS field) Local authorities (responsible for the transport systems at the urban and regional level) Representatives of business (traffic strategy management) and industry (manufacturers of ITS components). This book gathers selected papers presented at the 18th “Transport Systems. Theory and Practice” Scientific and Technical Conference organised by the Department of Transport Systems, Traffic Engineering and Logistics at the Faculty of Transport and Aviation Engineering of the Silesian University of Technology. The conference was held on 19-20 September 2022 in Katowice (Poland).Table of ContentsIdentification of Barriers to Ensuring Accessibility Standards for Tram Stops to the Needs of People with Disabilities.- The Use of Multi-Criteria Methods in the Problem of Selecting Vehicles for Oversize Cargo Transport.- Problems of Assessing the Technical Condition of Transport Means on the Example of the Means of Air Transport.- The Use of Automatic Passenger Counting Systems Data in Financial Settlement Models in Public Transport.- Comparative Analysis of Transport Tariffs and Operating Ticket Distribution Channels in Selected Agglomerations.- Commuter Rail Service Quality: A Case Study of Rhine-Ruhr Metropolitan Region.- Money is Not Everything - is Integrated Transport Only About Investments?.- Determination of Transport Plans in Urban Areas Considering Zero-Emission Vehicles.- Vehicle Choice for Sustainable Regional Railway.

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Book Synopsis

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