Intelligent Transport Systems Technologies and Applications
, by Perallos, Asier; Hernandez-Jayo, Unai; Onieva, Enrique; García Zuazola, Ignacio Julio
- ISBN: 9781118894781 | 1118894782
- Cover: Hardcover
- Copyright: 12/14/2015
INTELLIGENT TRANSPORT SYSTEMS
TECHNOLOGIES AND APPLICATIONS
This book provides a systematic overview of Intelligent Transportation Systems (ITS), offering an insight into the reference architectures developed within the main research projects. It delves into each of the layers of such architectures, from physical to application layer, describing the technological issues which are being currently faced by some of the most important ITS research groups. The book concludes with some end-user services and applications deployed by industrial partners.
The book is a well-balanced combination of academic contributions and industrial applications in the field of Intelligent Transportation Systems. It includes the most representative technologies and research results achieved by some of the most relevant research groups working on ITS, collated to show the chances of generating industrial solutions to be deployed in real transportation environments.
Dr Asier Perallos, University of Deusto, Spain
Asier Perallos hold a PhD and Bachelor in Computer Engineering from the University of Deusto. Since 1999 He has been working as a Lecturer in the Faculty of Engineering at the University of Deusto. His teaching focuses on software design and distributed systems, having taught several BSc, MSc and PhD courses.
Dr Unai Hernandez-Jayo, University of Deusto, Spain
Unai Hernandez Jayo completed his PhD in Telecommunications in 2012. He received his MSc degree in Telecommunication Engineering from the University of Deusto, Spain, in 2001.
Dr Ignacio Garcia Zuazola, University of Deusto, Spain
Ignacio Garcia Zuazola completed his PhD in Electronics (microwaves, antennas) part-time program in 2008 and his viva in 2010, a BENG (with honours) in Telecommunications Engineering from Queen Mary - University of London (2003), HND in Telecommunications Engineering from the college of North West London (2000), and FPII in Industrial Electronics from the School of Chemistry & Electronics of Indautxu, Spain (1995).
Dr Enrique Onieva, University of Deusto, Spain
Enrique Onieva received the B.E. degree in computer science engineering, the M.E. degree in soft computing and intelligent systems and the Ph.D. degree in computer science from the University of Granada, Spain, in 2006, 2008 and 2011, respectively.
About the Editors xv
List of Contributors xvii
Foreword xxiii
Acknowledgements xxxii
Part 1 Intelligent Transportation Systems 1
1 Reference ITS Architectures in Europe 3
Begoña Molinete, Sergio Campos, Ignacio (Iñaki) Olabarrieta and Ana Isabel Torre
1.1 Introduction 3
1.2 FRAME: The European ITS Framework Architecture 3
1.2.1 Background 4
1.2.2 Scope 5
1.2.3 Methodology and Content 6
1.3 Cooperative Systems and Their Impact on the European ITS Architecture Definition 7
1.3.1 Research Projects and Initiatives 7
1.3.2 Pilots and Field Operational Tests 8
1.3.3 European Policy and Standardization Framework 9
1.3.4 Impact on FRAME Architecture 9
1.4 Experiences in ITS Architecture Design 10
1.4.1 Cybercars‐2: Architecture Design for a Cooperative Cybernetics Transport System 10
1.4.2 MoveUs Cloud‐Based Platform Architecture 13
References 17
2 Architecture Reference of ITS in the USA 18
Clifford D. Heise
2.1 Introduction 18
2.2 National ITS Architecture in the USA 19
2.3 Origins of ITS Architecture in the USA 19
2.4 US National ITS Architecture Definition 20
2.4.1 The Development Process 20
2.4.2 User Services 22
2.4.3 Logical Architecture 22
2.4.4 Physical Architecture 23
2.4.5 Services 25
2.4.6 Standards Mapping 25
2.5 Impact on ITS Development in USA 26
2.5.1 Architecture and Standards Regulation 27
2.5.2 ITS Planning 28
2.5.3 ITS Project Development 29
2.5.4 Tools 32
2.6 Evolution of the National ITS Architecture 34
References 35
Part 2 Wireless Vehicular Communications 37
3 Wireless Communications in Vehicular Environments 39
Pekka Eloranta and Timo Sukuvaara
3.1 Background and History of Vehicular Networking 39
3.2 Vehicular Networking Approaches 46
3.3 Vehicular Ad‐hoc Networking 48
3.3.1 Vehicle‐to‐infrastructure Communication 50
3.3.2 Vehicle‐to‐vehicle Communication 51
3.3.3 Combined Vehicle‐to‐vehicle and Vehicle‐to‐infrastructure Communication 52
3.3.4 Hybrid Vehicular Network 53
3.3.5 LTE and Liquid Applications 54
References 55
4 The Case for Wireless Vehicular Communications Supported by Roadside Infrastructure 57
Tiago Meireles, José Fonseca and Joaquim Ferreira
4.1 Introduction 57
4.1.1 Rationale for Infrastructure‐based Vehicle Communications for Safety Applications 59
4.2 MAC Solutions for Safety Applications in Vehicular Communications 61
4.2.1 Infrastructure‐based Collision‐free MAC Protocols 63
4.2.2 RT‐WiFi – TDMA Layer 65
4.2.3 Vehicular Deterministic Access (VDA) 65
4.2.4 Self‐organizing TDMA (STDMA) 66
4.2.5 MS‐Aloha 66
4.3 Vehicular Flexible Time‐triggered Protocol 68
4.3.1 Model for RSU Deployment in Motorways 68
4.3.2 RSU Infrastructure Window (IW) 69
4.3.3 V‐FTT Protocol Overview 71
4.3.4 Synchronous OBU Window (SOW) 74
4.4 V‐FTT Protocol Details 75
4.4.1 Trigger Message Size 75
4.4.2 Synchronous OBU Window Length (lsow) 77
4.4.3 V‐FTT Protocol Using IEEE 802.11p/WAVE / ITS G‐5 78
4.5 Conclusions 80
References 81
5 Cyber Security Risk Analysis for Intelligent Transport Systems and In‐vehicle Networks 83
Alastair R. Ruddle and David D. Ward
5.1 Introduction 83
5.2 Automotive Cyber Security Vulnerabilities 84
5.2.1 Information Security 85
5.2.2 Electromagnetic Vulnerabilities 85
5.3 Standards and Guidelines 86
5.3.1 Risk Analysis Concepts 86
5.3.2 Functional Safety Standards 87
5.3.3 IT Security Standards 87
5.3.4 Combining Safety and Security Analysis 88
5.4 Threat Identification 88
5.4.1 Use Cases 88
5.4.2 Security Actors 89
5.4.3 Dark‐side Scenarios and Attack Trees 90
5.4.4 Identifying Security Requirements 93
5.5 Unified Analysis of Security and Safety Risks 93
5.5.1 Severity Classification 93
5.5.2 Probability Classification 95
5.5.3 Controllability Classification 95
5.5.4 Risk Classification 95
5.5.5 Evaluating Risk from Attack Trees 97
5.5.6 Prioritizing Security Functional Requirements 100
5.5.7 Security Assurance and Safety Integrity Requirements 101
5.6 Cyber Security Risk Management 102
5.7 Conclusions 103
Acknowledgements 104
References 104
6 Vehicle Interaction with Electromagnetic Fields and Implications for Intelligent Transport Systems (ITS) Development 107
Lester Low and Alastair R. Ruddle
6.1 Introduction 107
6.2 In‐vehicle EM Field Investigation and Channel Characterization 109
6.3 Field Simulation Tools and Techniques 112
6.4 In‐vehicle EM Field Measurement 116
6.5 Simulation of Field Distribution and Antenna Placement Optimization 118
6.6 Occupant Field Exposure and Possible Field Mitigation Methods 122
6.6.1 Human Exposure to Electromagnetic Fields 122
6.6.2 Field Mitigation Methods 125
6.7 Conclusions 127
Acknowledgements 128
References 128
7 Novel In‐car Integrated and Roof‐mounted Antennas 131
Rus Leelaratne†
7.1 Introduction 131
7.2 Antennas for Broadcast Radio 132
7.2.1 Roof‐mounted Radio Antennas 132
7.2.2 Hidden Glass Antennas 134
7.2.3 Hidden and Integrated Antennas 136
7.3 Antennas for Telematics 137
7.3.1 Roof‐mounted Telematics Antennas 137
7.3.2 Hidden Telematics Antennas 140
7.3.3 Future Trend of Telematics Antennas 141
7.4 Antennas for Intelligent Transportation Systems 141
7.4.1 Car2Car Communication Antennas 141
7.4.2 Emergency Call (E‐Call) Antennas 143
7.4.3 Other ITS Antennas 144
7.5 Intelligent and Smart Antennas 145
7.5.1 Intelligent Antenna for Broadcast Radio 145
7.5.2 Intelligent Antenna for GNSS 146
7.6 Conclusions 147
References 147
Part 3 Sensors Networks and Surveillance at ITS 149
8 Middleware Solution to Support ITS Services in IoT‐based Visual Sensor Networks 151
Matteo Petracca, Claudio Salvadori, Andrea Azzarà, Daniele Alessandrelli, Stefano Bocchino, Luca Maggiani and Paolo Pagano
8.1 Introduction 151
8.2 Visual Sensor Networks and IoT Protocols 153
8.2.1 Visual Sensor Networks 153
8.2.2 Internet of Things 156
8.3 Proposed Middleware Architecture for IoT‐based VSNs 158
8.3.1 RESTful Web Service 159
8.3.2 Configuration Manager 160
8.3.3 Resource Processing Engine 160
8.4 Middleware Instantiation for the Parking Lot Monitoring Use Case 161
8.4.1 Use Case Scenario, Exposed Resources and Their Interaction 161
8.4.2 Middleware Implementation 163
8.5 Conclusions 164
References 165
9 Smart Cameras for ITS in Urban Environment 167
Massimo Magrini, Davide Moroni, Gabriele Pieri and Ovidio Salvetti
9.1 Introduction 167
9.2 Applications to Urban Scenarios 169
9.3 Embedded Vision Nodes 171
9.3.1 Features of Available Vision Nodes 172
9.3.2 Computer Vision on Embedded Nodes 173
9.4 Implementation of Computer Vision Logics on Embedded Systems for ITS 175
9.4.1 Traffic Status and Level of Service 175
9.4.2 Parking Monitoring 178
9.5 Sensor Node Prototype 180
9.5.1 The Vision Board 181
9.5.2 The Networking Board 182
9.5.3 The Sensor 182
9.5.4 Energy Harvesting and Housing 182
9.5.5 The Board Layout 183
9.6 Application Scenarios and Experimental Results 184
9.7 Conclusions 185
References 187
Part 4 Data Processing Techniques at ITS 189
10 Congestion Prediction by Means of Fuzzy Logic and Genetic Algorithms 191
Xiao Zhang, Enrique Onieva, Victor C.S. Lee and Kai Liu
10.1 Introduction 191
10.2 Hierarchical Fuzzy Rule‐based System (HFRBS) 193
10.3 Genetic Hierarchical Fuzzy Rule‐based System (GHFRBS) 194
10.3.1 Triple Coding Scheme 194
10.3.2 Genetic Operators 196
10.3.3 Chromosome Evaluation 197
10.3.4 Mechanism and Characteristics of the Algorithm Framework 197
10.4 Dataset Configuration and Simplification 197
10.5 Experimentation 199
10.5.1 Experimental Setup 199
10.5.2 Results 199
10.5.3 Analysis of the Results 201
10.6 Conclusions 202
Acknowledgment 203
References 203
11 Vehicle Control in ADAS Applications: State of the Art 206
Joshué Pérez, David Gonzalez and Vicente Milanés
11.1 Introduction 206
11.2 Vehicle Control in ADAS Application 206
11.3 Control Levels 207
11.4 Some Previous Works 208
11.5 Key Factor for Vehicle Control in the Market 210
11.6 ADAS Application From a Control Perspective 211
11.6.1 Lane Change Assistant Systems 212
11.6.2 Pedestrian Safety Systems 212
11.6.3 Forward‐looking Systems 213
11.6.4 Adaptive Light Control 213
11.6.5 Park Assistant 214
11.6.6 Night Vision Systems 215
11.6.7 Cruise Control System 215
11.6.8 Traffic Sign and Traffic Light Recognition 215
11.6.9 Map Supported Systems 216
11.6.10 Vehicle Interior Observation 217
11.7 Conclusions 217
References 218
12 Review of Legal Aspects Relating to Advanced Driver Assistance Systems 220
Alastair R. Ruddle and Lester Low
12.1 Introduction 220
12.2 Vehicle Type Approval 221
12.3 Trends in Vehicle Automation 223
12.3.1 EU Policy 223
12.3.2 Brake Assist Systems 223
12.3.3 Advanced Vehicle Systems 225
12.3.4 Advanced Driving Assistance Systems 226
12.3.5 Categorization of Vehicle Automation Levels 227
12.4 Vienna Convention on Road Traffic 227
12.4.1 Implications for Driving Assistance Systems 230
12.4.2 Proposed Amendments 231
12.4.3 Implications for Autonomous Driving 233
12.5 Liability Issues 234
12.5.1 Identifying Responsibilities 234
12.5.2 Event Data Recorders 236
12.6 Best Practice for Complex Systems Development 237
12.6.1 Safety Case 238
12.6.2 Safety Development Processes 239
12.6.3 ECWVTA Requirements 240
12.6.4 Cyber Security Issues 241
12.7 Conclusions 242
Acknowledgements 243
References 243
Part 5 Applications and Services for Users and Traffic Managers 247
13 Traffic Management Systems 249
António Amador, Rui Dias, Tiago Dias and Tomé Canas
13.1 Introduction 249
13.1.1 Objectives 249
13.1.2 Traffic Management 250
13.1.3 Traffic Environments 251
13.2 Traffic Management Framework 253
13.2.1 Inputs 255
13.2.2 Analysis 260
13.2.3 Outputs 265
13.3 Key Stakeholders 266
13.4 Traffic Management Centres 266
13.4.1 Scope 267
13.4.2 Operation Platforms 268
13.5 Conclusions 270
References 271
14 The Use of Cooperative ITS in Urban Traffic Management 272
Sadko Mand?uka, Edouard Ivanjko, Miroslav Vujić, Pero Škorput and Martin Gregurić
14.1 Introduction 272
14.2 Cooperative Ramp Metering 274
14.2.1 Ramp Metering 275
14.2.2 Cooperation between Local Ramp Meters 277
14.2.3 Cooperation between Ramp Metering and Other Traffic Management Systems 278
14.3 Incident Management in Urban Areas 280
14.4 Public Transport Cooperative Priorities 284
14.5 Conclusions 287
Acknowledgment 287
References 288
15 Methodology for an Intelligent in‐Car Traffic Information Management System 289
Nerea Aguiriano, Alfonso Brazalez and Luis Matey
15.1 Introduction 289
15.2 Validation Framework 291
15.3 HMI Design Methodology 292
15.3.1 Signal Model 295
15.3.2 Interpretation Model 296
15.3.3 Representation Model 302
15.4 Case Study 305
15.4.1 Signal Model for Received Messages 305
15.4.2 Interpretation Model 306
15.4.3 Representation Model 310
15.5 Conclusions 311
References 311
16 New Approaches in User Services Development for Multimodal Trip Planning 313
Asier Moreno, Itziar Salaberria and Diego López‐de‐Ipiña
16.1 Introduction 313
16.1.1 Multimodal Transport 314
16.1.2 Travel User Services 315
16.2 Travel Planning Information Systems 316
16.2.1 Standard Travel Planning Services 316
16.2.2 Transit Information Formats and Standards 319
16.2.3 New Trends in Transit Information 320
16.3 Integrating Linked Open Data for Multimodal Transportation 321
16.3.1 Related Work 323
16.3.2 Management and Provision of Multimodal Transport Semantic Information 324
16.4 Conclusions 328
References 329
Index 331
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