Connected and Autonomous Vehicles in Smart Cities

Description

This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems. Cover Half Title Title Page Copyright Page Table of Contents Preface Editor Contributors Chapter 1 Connected and Autonomous Electric Vehicle Charging Infrastructure Integration to Microgrids in Future Smart Cities 1.1 Introduction 1.1.1 Smart Cities 1.1.2 Microgrids 1.1.3 Renewable Energy Generation Resources 1.1.3.1 SP 1.1.3.2 Wind Turbines 1.1.3.3 Mini-hydro 1.1.4 Energy Trading among Microgrids 1.2 CAEVs and the Effect of Integrating CAEVs to Microgrids 1.3 Microgrid Control Methods in the Presence of CAEVs 1.3.1 Microgrid Centralized Control 1.3.2 Microgrid Decentralized Control 1.3.3 Microgrid Distributed Control 1.4 Quality of Service in Plug-in Electric Vehicle Charging Infrastructure 1.5 Performance Evaluation 1.6 Challenges and Future Directions 1.7 Conclusion References Chapter 2 A Hierarchical Management Framework for Autonomous Electric Mobility-on-Demand Services 2.1 Introduction 2.1.1 Overview 2.1.2 21st Century Urban Transportation System 2.1.3 AEMoDs: Opportunities and Challenges 2.1.4 Contributions 2.2 Smart Dispatching and Routing of AEMoDs 2.2.1 Queuing Model 2.2.2 System Parameters 2.3 Lower Layer 2.3.1 Multiclass Charging and Dispatching 2.3.1.1 System Stability Conditions 2.3.1.2 Maximum Response Time Optimization Problem Formulation 2.3.1.3 Optimal Dispatching and Charging Decisions 2.3.1.4 Maximum Expected Response Time 2.3.1.5 Average Response Time Optimization Problem Formulation 2.3.1.6 Optimal Dispatching and Charging Decision 2.3.1.7 Simulation Results 2.3.2 Multiclass Dispatching with Subclass Charging 2.3.2.1 Stability Conditions 2.3.2.2 Subclass Charging and Dispatching Optimization Problem Formulation 2.3.2.3 Lower Bound Analytical Solutions 2.3.2.4 Simulation Results Analysis 2.4 Middle Layer: Optimal Vehicle Dimensioning 2.4.1 System Stability and Response Time Limit Conditions 2.4.2 Optimal Vehicle Dimensioning Problem Formulation 2.4.2.1 Lower-Bound Solution 2.4.2.2 Solution Tightening 2.4.3 Simulation Results 2.5 Upper Layer: Fleet Rebalancing with In-route Charging 2.5.1 System Stability Conditions 2.5.2 Maximum Response Time Optimization Problem Formulation 2.5.3 Optimal Rebalancing and Charging Decisions 2.5.4 Maximum Expected Response Time 2.5.5 Simulation Results 2.6 Conclusion References Chapter 3 Multifaceted Synthesis of Autonomous Vehicles’ Emerging Landscape 3.1 Introduction 3.2 Benefits 3.2.1 Safety 3.2.2 Vehicle Kilometers Traveled (VKT), Vehicle Ownership, and Congestion 3.2.3 Better Equity and Potential Job Loss 3.2.4 System Capacity 3.2.5 Parking Spaces 3.2.6 Energy and Emissions 3.2.7 System and Policies 3.2.8 Summary of AVs’ Benefits and Impacts 3.3 Economic Benefits and Societal Impacts 3.4 Implication of AVs on Travel Behavior and Development of Cities 3.4.1 Travel Behavior 3.4.2 Travel Cost and Affordability 3.4.3 Penetration Rate and Fleet Size 3.4.4 Parking Strategy and Demand 3.4.5 Summary of AV Implications 3.5 User Opinions, Adoption, and Perceptions 3.5.1 Effect of Awareness/Previous Experience on Public Opinion 3.5.2 Country/National Level Insights 3.5.3 Synopsis on Truck Drivers 3.5.4 Perceived Benefits and Implications 3.5.5 View of State of Technology 3.5.6 Effect of Socioeconomic and Demographics 3.5.7 Affordability and Willingness to Pay/Own 3.5.8 Summary of Public Opinions and Perception about AVs 3.6 Challenges Associated with AVs 3.6.1 Accuracy 3.6.2 Liability and Regulations 3.6.3 Ethics 3.6.4 AVs’ Accidents 3.7 Infrastructure Requirements and Implications 3.7.1 Traffic Management 3.7.2 Lane Marking and Signage 3.7.3 Potential Need for Safe Harbor Areas 3.7.4 Design of Parking for CAVs 3.7.5 Fuel and Power Distribution 3.7.6 Impact on Bridges 3.7.7 Internet and Connectivity 3.7.8 Road Geometry 3.8 Synopsis on Pilots and Laws and Regulations 3.9 New Value Network and New Business Models 3.10 Framework for Incorporating AVs into the Realm of Smart Cities References Chapter 4 Machine Learning Methodologies for Electric-Vehicle Energy Management Strategies: A Comprehensive Survey 4.1 Introduction 4.2 Rule-Based and Optimization-Based EMSs for EVs/HEVs 4.2.1 Rule-Based EMS for EVs/HEVs 4.2.2 Optimization-Based EMS for EVs/HEVs 4.3 Machine Learning-Based Tools for EV Energy Management 4.3.1 Prediction-Based EMS for EVs 4.3.2 Learning-Based EMS for EVs 4.4 Conclusions and Future Directions Acknowledgment Appendix A References Chapter 5 Dynamic Road Management in the Era of CAV 5.1 Introduction 5.1.1 Road Traffic Problems 5.1.2 Conventional and Emerging Congestion Mitigation Methodologies 5.1.3 Connected Vehicles and Infrastructure 5.1.4 Scope and Organization 5.2 DTM Challenges 5.2.1 Data Collection 5.2.2 Road Configuration 5.2.3 Communication and Control 5.2.4 Traffic Assignment 5.3 CAV-Enabled Traffic Management 5.3.1 Autonomous Intersection Management 5.3.2 Adaptive Traffic Light Control 5.3.3 Dynamic Lane Grouping 5.3.4 Dynamic Lane Reversal 5.3.5 Dynamic Trajectory Planning 5.4 Smart Road Vision and Practical Issues 5.4.1 Support of Human-Driven Vehicles 5.4.2 Optimized Route Selection in Mixed Traffic 5.5 Conclusion and Open Research Problems Acknowledgment References Chapter 6 VANET Communication and Mobility Sustainability: Interactions and Mutual Impacts in Vehicular Environment 6.1 Introduction 6.2 Mobility and Traffic Engineering Fundamentals 6.2.1 Car-Following Behaviour 6.2.2 Traffic Modelling Techniques 6.2.3 Traffic Navigation 6.2.4 Eco-Routing Navigation 6.2.5 Eco-Routing Considering Ideal Communication 6.3 VANET Communication 6.3.1 VANET Characteristics 6.3.2 VANET Challenges 6.3.3 Physical Specifications of VANET 6.4 Modelling VANET Communication in Large-Scale Networks 6.4.1 Modelling the WAVE Medium Access Technique 6.4.1.1 MAC Operation in WAVE 6.4.1.2 Representing the System in Markov Model and Its Solution 6.4.2 MAC Queuing Using the M/M/1/K Model 6.4.3 Communication Model Validation 6.5 Modelling Eco-Routing and VANET 6.5.1 The INTEGRATION Software 6.5.2 Eco-Routing with Realistic VANET Communication Modelling 6.6 Simulation and Results 6.6.1 The Ideal Communication Case 6.6.1.1 Impact of Penetration Rate on Fuel Consumption 6.6.1.2 Penetration Rate and Congestion Levels 6.6.2 Realistic Communication Case 6.6.2.1 RSU Allocation 6.6.2.2 Communication System Impact on Eco-Routing System Performance 6.6.2.3 Quantifying the Realistic Communication Impact on Mobility Sustainability 6.6.2.4 Impact of Realistic Communication and Penetration Ratio 6.7 Conclusion References Chapter 7 Message Dissemination in Connected Vehicles 7.1 Background Work 7.1.1 Dissemination of Messages Using Vehicular Cloud Computing 7.1.2 Dissemination of Messages Using Vehicular Fog Computing 7.2 Hybrid-Vehcloud Message Dissemination 7.2.1 Dissemination of Messages Using Hybrid-Vehcloud 7.2.2 Hybrid-Vehcloud Message Dissemination Algorithm 7.3 DFCV Message Dissemination 7.3.1 DFCV Message Dissemination Technique 7.3.2 DFCV Message Dissemination Algorithm 7.4 Performance Evaluation 7.4.1 Simulation Setup 7.4.2 Performance Metrics 7.4.3 Performance Evaluation of Hybrid-Vehcloud 7.4.4 Performance Evaluation of DFCV 7.5 Comparison of Vehicular Fog Computing and Vehicular Cloud Computing 7.5.1 Advantages of Vehicular Fog Computing over Vehicular Cloud Computing 7.5.2 Advantages of Vehicular Cloud Computing over Vehicular Fog Computing 7.6 Conclusion 7.7 Future Directions References Chapter 8 Exploring Cloud Virtualization over Vehicular Networks with Mobility Support 8.1 Introduction 8.2 Vehicular Networks 8.2.1 Mobility Management 8.3 Softwarization and Virtualization 8.4 System Design 8.5 Use Cases 8.5.1 SURROGATES 8.5.1.1 Concept 8.5.1.2 Operation 8.5.1.3 Implementation 8.5.1.4 Performance Evaluation 8.5.2 CAVICO 8.5.2.1 Concept 8.5.2.2 Operation 8.5.2.3 Performance Evaluation 8.5.3 VRU-Safe 8.5.3.1 Concept 8.5.3.2 Implementation 8.5.3.3 Performance Evaluation 8.5.4 5G-CAGE 8.5.4.1 Concept 8.5.4.2 Implementation 8.5.4.3 Performance Evaluation 8.6 Research Challenges 8.7 Conclusions Acknowledgment References Chapter 9 Data Offloading Approaches for Vehicle-to-Everything (V2X) Communications in 5G and Beyond 9.1 Introduction 9.2 A Brief Overview of 5G, V2X Communications and Applications 9.3 Challenges on Resource Allocation and Motivation 9.4 Possible Solution Approaches 9.5 Workload Offloading Approaches for V2X Communications in 5G 9.5.1 Computation Offloading 9.5.2 Data Traffic Workload Offloading 9.5.2.1 Centralized/Cloud-Based Workload Offloading 9.5.2.2 Distributed Based Workload Offloading 9.5.2.3 Selected Vehicle-Based Workload Offloading 9.6 Summary References Chapter 10 Connected Unmanned Aerial Vehicles for Flexible Coverage, Data Gathering and Emergency Scenarios 10.1 Introduction 10.2 Architectures for Networks of Drones 10.2.1 Centralized-Mesh Network Architecture 10.2.2 UAV Ad Hoc Network Architecture 10.2.3 Multi-Group UAV Network Architecture 10.2.4 Multi-Layer UAV Ad Hoc Network Architecture 10.3 Simulation Setup 10.4 Performance Evaluation and Discussion 10.5 Conclusion Acknowledgement References Chapter 11 Localization for Vehicular Ad Hoc Network and Autonomous Vehicles, Are We Done Yet? 11.1 Introduction 11.2 Standard Localization System in CAVs 11.3 Perception and Sensors 11.3.1 Ultrasound Technology 11.3.2 Front and Rear Radar Sensors 11.3.3 Camera and Visual Sensor 11.3.4 LiDAR, Laser and Infrared Sensors 11.3.5 Autonomous Vehicle Networks 11.4 Localization System Designs for Autonomous Driving 11.4.1 Global Positioning System (GPS) 11.4.2 Map Matching 11.4.2.1 Incremental Method 11.4.2.2 Global Method 11.4.2.3 Statistical Method 11.4.2.4 Fuzzy Logic-Based Algorithms 11.4.3 Cellular Localization 11.4.3.1 Ranging Method 11.4.3.2 Limitation of Cellular Localization Accuracy 11.4.4 Image and Video Localization Technique 11.4.5 Dead Reckoning 11.4.6 Distributed Ad Hoc Localization 11.5 Simultaneous Localization and Mapping (SLAM) 11.5.1 Filtering Solutions 11.5.2 Monte Carlo Solutions 11.5.3 Smoothing and Mapping (Loop Closure) 11.5.4 iSAM and GraphSLAM 11.6 Cooperative Estimation, Filtering, and Sensor Fusion 11.7 Localization Systems in Use for Autonomous Driving 11.7.1 Application for Accurate Location-Aware 11.7.2 Cooperative Intersection Safety Applications 11.7.3 Cooperative Adaptive Cruise Control Application 11.7.4 Platooning Application 11.7.5 Application for High Accurate Location-Aware 11.7.6 Application for Inaccurate Location-Aware 11.7.7 VETRAC 11.8 Conclusion References Chapter 12 Automotive Radar Signal Analysis 12.1 Automotive Radar 12.1.1 Assisted Driver Sensors 12.1.2 Significance 12.2 Waveforms in Automotive Radars 12.2.1 Triangular FMCW Waveform 12.2.1.1 Triangular FMCW Simulation 12.2.2 Trapezoidal FMCW Waveform 12.2.3 Sawtooth FMCW Waveform 12.2.3.1 Range, Velocity and Angle Estimation 12.2.4 FMCW System Resolution and Performance 12.2.4.1 Range Resolution 12.2.4.2 Velocity Resolution 12.2.4.3 Angle Resolution 12.2.5 OFDM Waveform 12.2.5.1 System Model 12.2.5.2 Range and Velocity Estimation 12.2.5.3 Waveform Construction 12.2.5.4 OFDM Simulation 12.3 MIMO Radar Summary Triangular FMCW Matlab Simulation Code References Chapter 13 Multisensor Precise Positioning for Automated and Connected Vehicles 13.1 Positioning of Automated Vehicles 13.2 Different Sensors for AV/CV Positioning 13.2.1 Global Navigation Satellite Systems 13.2.2 Inertial Navigation Systems 13.2.3 Odometers 13.2.4 Perception Systems 13.2.5 Sensors Utilization under Different Driving Conditions 13.3 Multisensor Fusion for Positioning 13.3.1 Multisensor Fusion Filters 13.3.1.1 The Kalman Filter 13.3.1.2 The Particle Filter 13.3.2 Multisensor Fusion Architectures 13.3.2.1 GNSS/INS Integration Architectures 13.3.2.2 General Integration Architectures 13.4 PPP/INS Integration: A Case Study for Automated Level 2 Driving 13.4.1 Precise Point Positioning 13.4.1.1 Standard Dual-frequency PPP 13.4.1.2 Single-Frequency PPP 13.4.2 SF-PPP/INS Integration 13.4.2.1 Methodology 13.4.2.2 Results and Discussion 13.5 Summary References Chapter 14 Deploying Wireless Charging Systems for Connected and Autonomous Electric Vehicles 14.1 Introduction 14.2 Preliminary 14.2.1 Connected and Autonomous Electric Vehicles 14.3 Wireless Charging Systems 14.3.1 Types of Wireless EV Charging 14.4 Standardization for Wireless EV Charging 14.4.1 ISO/IEC 15118 Standard 14.4.1.1 Wireless Communication Requirements 14.4.2 SAE J2954 Standard 14.4.2.1 Overviews of J2954 WPT System and Charging Process 14.4.3 Other WEVC Standards 14.4.3.1 IEC 61980 Standards 14.4.3.2 ISO/PAS 19363 Standard 14.4.3.3 SAE J2847/6 Standard 14.5 CAEV Charging Management System 14.5.1 Automated Reservation Mechanism 14.5.2 SecCharge Test Bed for SWC System 14.6 Summary Acknowledgment References Chapter 15 Dynamic Wireless Charging of Electric Vehicles 15.1 Introduction 15.2 Literature Review 15.3 Electric Vehicles and Dynamic Charging 15.4 Wireless Power Transfer (WPT) 15.4.1 WPT Principles 15.4.2 WPT System 15.4.3 Analysis of WPT 15.5 Dynamic Wireless Power Transfer 15.5.1 DWPT System 15.5.2 DWPT Analysis 15.5.3 Design Considerations 15.6 Optimal Performance of DWPT Systems 15.6.1 Maximum Efficiency and Optimal Frequency 15.6.2 Load Matching 15.7 Control System 15.7.1 Output Voltage Regulation 15.7.2 Maximum Efficiency Achievement 15.7.2.1 Resonant Parameter Independent Method 15.7.2.2 Coupling Coefficient Estimation-Based Method 15.8 Future Outlook Acknowledgment References Chapter 16 Wirelessly Powered Unmanned Aerial Vehicles (UAVs) in Smart City 16.1 Introduction 16.2 UAVs in Smart City 16.3 Energy Efficiency and Connectivity of UAVs 16.4 Wireless Power Transfer for UAVs 16.5 WPT-BPL for UAVs 16.5.1 Induction of magnetically coupled circuit 16.5.2 Design Issues and Performance Analysis 16.5.2.1 Output Power Analysis 16.5.2.2 Design for Broadband Communication 16.5.3 2D and 3D Power and Data Channel 16.6 Conclusion Acknowledgment References Chapter 17 Cyber Security Considerations for Automated Electro-Mobility Services in Smart Cities 17.1 Introduction 17.2 Connected and Autonomous Electric Vehicles 17.3 Automated Electro-Mobility Services 17.3.1 Peer-to-Peer Car-Sharing Services 17.4 Cyber Security for AEM Services 17.4.1 Security Goals 17.4.2 Potential Threats 17.4.3 Security Requirements 17.5 Proposed Security Solution for P2P Car-Sharing System 17.5.1 Issues and Challenges 17.5.2 Security Considerations 17.5.3 Conjugated Authentication and Authorization 17.5.3.1 Entity Authentication 17.5.3.2 Authenticated Prior Binding 17.5.4 Token-Based Authentication and Authorization 17.5.4.1 Token Generation Phases 17.5.4.2 Validation Phase 17.6 Summary Acknowledgment References Chapter 18 Incentivized and Secure Blockchain-based Firmware Update and Dissemination for Autonomous Vehicles 18.1 Introduction 18.1.1 Contributions 18.2 Literature Review 18.3 Preliminaries 18.3.1 Blockchain and Smart Contracts 18.3.2 Cryptographic Tools 18.3.2.1 Attribute-Based Encryption 18.3.2.2 Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) 18.3.2.3 Aggregate Signatures 18.4 Proposed System 18.4.1 System Architecture 18.4.2 System Initialization 18.4.3 Smart Contract Creation 18.4.4 Firmware Update Dissemination 18.4.5 Rewarding 18.5 Performance Evaluations 18.5.1 On-Chain Cost 18.5.1.1 Methodology/Experiment Setup 18.5.1.2 Performance Metrics 18.5.1.3 Results and Discussion 18.5.2 Off-Chain Cost 18.6 Security Analysis 18.7 Conclusion Acknowledgment References Index