Current Technologies in Vehicular Communication (eBook)

Dr. George J. Dimitrakopoulos is an assistant professor at the Department of Informatics and Telematics of the Harokopio University of Athens, Greece. He received his bachelor’s degree in electrical and computer engineering from the National Technical University of Athens in 2002. He received his PhD in Digital systems from the University of Piraeus in 2007.

Preface 5
Contents 7
List of Figures 10
Chapter 1: Introduction: The History of Vehicular Communications 12
1.1 Goals 12
1.2 Motivation: Transportation and Its Drawbacks 12
1.3 Overview of Latest Advances in Transportation Research 13
1.3.1 Transport Mode Rail 13
1.3.2 Transport Mode Road 14
1.3.3 Transport Mode Air 16
1.3.4 Transport Mode Waterway/Sea 17
1.3.5 Intermodal Transport 18
1.4 Road Transport: Utilization of ICT in Vehicles: Intelligent Transport Systems (ITS) 20
1.5 Conclusions 22
1.6 Review Questions 22
Chapter 2: Vehicular Communications Standards 24
2.1 Goals 24
2.2 Introduction 24
2.3 Wireless Access for Vehicular Environments (WAVE) and Its Migration Towards IEEE 802.11p 25
2.3.1 Safety-Oriented 26
2.3.2 Traffic Control-Oriented 27
2.3.3 User Comfort-Oriented 27
2.4 IEEE 1609 28
2.5 SAE J2735 29
2.6 LED-Enabled Visible Light Communications (IEEE TG 802.15.7) 30
2.7 Bluetooth 32
2.8 2G and 3G Mobile Communication Infrastructures 34
2.9 4G/5G-D2D 35
2.9.1 Concept Overview 35
2.9.2 Information Sources 37
2.9.3 Example Data to Be Aggregated 38
2.9.4 Processing and Outcomes 38
2.9.5 Benefits of Framework 39
2.9.6 Operational Scenarios 40
2.9.6.1 Scenario 1: Collision Avoidance 40
2.9.6.2 Scenario 2: Automated Route Guidance for Emergency Response Vehicles 42
2.9.6.3 Scenario 3: Advanced Assisted Eco-Driving 42
2.10 ETSI and CEN Standards for V2X Communications 43
2.11 Conclusions 44
2.12 Review Questions 44
Chapter 3: Sustainable Mobility in Smart Cities: Traffic Assessment, Forecasting, and Management 45
3.1 Goals 45
3.2 Urban Transportation Inefficiencies 45
3.3 Smart Cities and Smart City Operations (SCOs) 46
3.3.1 Basic Definitions 46
3.3.2 SCOs Challenges 47
3.3.2.1 Level of Intelligence (“Smartness”) Required 47
3.3.2.2 Technology 48
3.3.2.3 Scalability of Smart Solutions 49
3.3.2.4 Formulation of City-Specific Objectives 49
3.3.2.5 Economic Growth 50
3.3.2.6 Management and Organization 50
3.4 Sustainable Mobility: Mobility as a Service (MaaS) 51
3.5 Case Studies 52
3.5.1 Traffic Assessment, Forecasting, and Management Applications (TAFM) 52
3.5.2 Road Luminosity Management Applications 53
3.5.3 Car Pooling (Ride-Sharing) 54
3.5.3.1 Business Case 54
3.5.3.2 Formal Description 57
Input 57
Objective and Solution 59
3.5.3.3 Results 60
Scenario 1: Regular Service 60
Robust Discovery Phase 61
Decision-Making Phase 62
Scenario 2: Cost-Driven Scenario 64
Robust Discovery Phase 64
Decision-Making Phase 65
Scenario 3: Improvement of Driver 66
Robust Discovery Phase 67
Decision-Making Phase 68
3.5.4 Intelligent Parking Management 69
3.6 Conclusions 70
3.7 Review Questions 71
Chapter 4: Advanced Driver Assistance Systems (ADAS) 72
4.1 Goals 72
4.2 Introduction 72
4.3 Cooperative Mobility and Cooperative Driving 73
4.4 Green (eco) Driving 74
4.5 Connectivity in Road Transport 75
4.6 Information Sharing for Sustainable Multimodal Transport 76
4.7 Case Studies 77
4.7.1 Proactive Global Alerting Systems 77
4.7.1.1 Formulation 77
4.7.1.2 Solution: Warning Functions 81
Minimum Distance Warning 81
Safe Following Distance Warning 82
Safe Front-Side Distance Warning 86
Congestion Ahead Warning 88
4.7.2 Reconfigurable Driving Styles 91
4.7.2.1 Introduction 91
4.7.2.2 Formal Description 92
Decision-Making Phase: Exploitation of Knowledge 94
4.7.3 Video-Based DAS 95
4.7.4 Radar-Based DAS 95
4.7.5 Head-up Display-Based DAS 96
4.7.6 Driver Fatigue Detection Systems 98
4.7.6.1 Visual Features 99
4.7.6.2 Nonvisual Features 100
4.7.7 Obstacle Recognition 100
4.7.8 Distraction Detection 101
4.7.9 Lane Keeping and Lane Departing 103
4.7.10 Proactive Emergency Braking 103
4.7.11 Remote Vehicle Monitoring 104
4.8 Conclusions 104
4.9 Review Questions 105
Chapter 5: ICT-Enabled, Knowledge-Based (Cognitive) Management Algorithms for ADAS 106
5.1 Goals 106
5.2 Introduction 106
5.3 The Current Wireless Landscape: Towards Cognitive Systems 107
5.4 Wireless Sensor Networks (WSNs) 109
5.5 Cognitive Management Systems 110
5.5.1 General Characteristics 110
5.5.2 Contextual Acquisition 111
5.5.3 Profiles Derivation 112
5.5.4 Policies Extraction 112
5.5.5 Output 112
5.5.6 Cognitive Features 112
5.6 Management Functionality Approaches for ADAS 113
5.6.1 High-Level Approach 113
5.6.2 Requirements 114
5.6.3 Indicative Architecture and Description of Components 115
5.6.4 Vehicle Sensors and WSNs 115
5.6.5 Vehicle Cognitive Management Functionality (V-CMF) 116
5.6.6 Infrastructure Cognitive Management Functionality (I-CMF) 117
5.6.7 Indicative Information Flow 118
5.7 Conclusions 119
5.8 Review Questions 119
Chapter 6: The Future: Towards Autonomous Driving 121
6.1 Goal of Chapter 121
6.2 Highly Automated Driving 121
6.3 Autonomous Driving 122
6.3.1 Introduction 122
6.3.2 Advantages 123
6.3.3 Disadvantages and Obstacles 124
6.3.4 Legislation and Political Decisions 125
6.3.5 The Way to the Future 126
6.4 Conclusions 127
6.5 Review Questions 129