Computation and Big Data for Transport (eBook)

Digital Innovations in Surface and Air Transport Systems

Pedro Diez, Pekka Neittaanmäki, Jacques Periaux, Tero Tuovinen, Jordi Pons-Prats (Herausgeber)

eBook Download: PDF

2020 | 1. Auflage
252 Seiten
Springer-Verlag
978-3-030-37752-6 (ISBN)

Infos

This book gathers the outcomes of the second ECCOMAS CM3 Conference series on transport, which addressed the main challenges and opportunities that computation and big data represent for transport and mobility in the automotive, logistics, aeronautics and marine-maritime fields. Through a series of plenary lectures and mini-forums with lectures followed by question-and-answer sessions, the conference explored potential solutions and innovations to improve transport and mobility in surface and air applications. 

The book seeks to answer the question of how computational research in transport can provide innovative solutions to Green Transportation challenges identified in the ambitious Horizon 2020 program. In particular, the respective papers present the state of the art in transport modeling, simulation and optimization in the fields of maritime, aeronautics, automotive and logistics research. In addition, the content includes two white papers on transport challenges and prospects. 

Given its scope, the book will be of interest to students, researchers, engineers and practitioners whose work involves the implementation of Intelligent Transport Systems (ITS) software for the optimal use of roads, including safety and security, traffic and travel data, surface and air traffic management, and freight logistics.

Inhalt

Foreword 6
Preface 8
Contents 10
Contributors 12
Part I White Paper 16
1 Digital Technologies for Transport and Mobility: Challenges, Trends and Perspectives 17
1.1 Introduction 18
1.2 Surface Transport 19
1.2.1 Current Situation and Challenges 19
1.2.2 Trends 20
1.2.3 Perspectives/Recommendations 21
1.3 Aeronautics and Aviation 22
1.3.1 Current Situation and Challenges 22
1.3.2 Challenges for Improved Aircraft Design 23
1.3.3 Trends 24
1.3.4 Perspectives 26
1.4 Cyber Security—Transport and Logistics in a Time of (cyber) Insecurity 27
1.4.1 Current Situation and Challenges 27
1.4.2 Trends 28
1.4.3 Perspectives/Recommendations 30
Part II Reviews and Perspectives 31
2 Cyber Security in Aviation, Maritime and Automotive 32
2.1 Introduction 33
2.2 Aviation 33
2.3 Maritime 36
2.4 Automotive 39
2.5 Conclusion 42
References 44
3 Operation of Transport and Logistics in a Time of (Cyber)Insecurity 46
3.1 The Operational Technology Security Problem 47
3.2 Cyber Defense 47
3.2.1 Standards and Controls 48
3.2.2 Cyber Security and Institutional Preparedness 50
3.2.3 Authentication and Access Control 51
3.2.4 Cryptography and Encryption 52
3.2.5 Network Security 53
3.2.6 Computer and Software Security 54
3.2.7 Cyber Intelligence 55
3.3 Managing Transport Cybersecurity 56
3.3.1 Getting from A to B Autonomously—A Case 56
3.3.2 Managed Risk, Infrastructure, and Seeking Remedy 58
3.3.3 Protecting Valued Information and Communications 59
3.3.4 The Geopolitical-Economic Driver 60
3.3.5 Notes on Managing Risk 60
References 61
4 New Data and Methods for Modelling Future Urban Travel Demand: A State of the Art Review 63
4.1 Introduction 63
4.2 Understanding Urban Mobility 65
4.2.1 Trends in Relevant Variables for Travel Demand Modelling 65
4.2.2 New Data Sources and Collection Methods 67
4.3 Urban Travel Demand Modelling Framework 69
4.3.1 The Classical Four-Step Models 69
4.3.2 Activity-Based Models 70
4.3.3 Agent-Based Models 71
4.3.4 Integrated Models and New Transport Services 72
4.4 Discussion and Possible Lines of Research 73
References 75
5 Maritime Transport and the Threat of Bio Invasion and the Spread of Infectious Disease 80
5.1 Introduction 81
5.2 Biological Invasion 81
5.3 Infectious Disease 82
5.4 Vector Borne Disease 82
5.5 Aedes Mosquitos 83
5.6 Modeling Considerations 83
References 84
Part III Computational Methods and Applications 85
6 Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems 86
6.1 Introduction 86
6.2 CVRP Feature Extraction 88
6.2.1 Role of Features in VRP 88
6.2.2 Data 89
6.3 The Analysis Process 92
6.4 Results 95
6.4.1 Step 0 95
6.4.2 Step 1 95
6.4.3 Step 2 97
6.4.4 Step 3 98
6.4.5 Summary of Results 104
6.5 Discussion 104
References 108
7 A New Multi-objective Solution Approach Using ModeFRONTIER and OpenTrack for Energy-Efficient Train Timetabling Problem 112
7.1 Introduction 113
7.2 Literature Review 114
7.3 ModeFRONTIER and OpenTrack 117
7.4 Case Study 119
7.5 Solution Approach 121
7.6 Application 123
7.6.1 ModeFRONTIER Workflow 123
7.6.2 Results 125
7.7 Conclusion 127
References 127
8 Development of New Lagrangian Computational Methods for Ice-Ship Interaction Problems: NICESHIP Project 129
8.1 Introduction 130
8.1.1 Navigation in the Arctic Area 130
8.1.2 The Design of Ships for Navigation in Ice 131
8.1.3 History and State of the Art in Simulation and Analysis of Ship Navigation in Ice 132
8.2 NICE-SHIP Project Scenarios 133
8.2.1 Scenario 1: Analysis of the Icebreaking Performance of Ships in Level Ice 134
8.2.2 Scenario 2: Analysis of the Performance of Ships in Brash Ice 147
8.3 Conclusions 160
References 160
9 Delivery Service in Congested Urban Areas 162
9.1 Introduction 163
9.2 Congested Urban Traffic Area 163
9.3 Approaches, Models, Methods 164
9.4 Estimation of Traffic Flow Assignment 165
9.5 Travel Demands in an Urban Area 168
9.6 Delivery Route Planning Under Conditions of Urban Congestions 170
9.7 Conclusion 171
References 172
Part IV Translational Research 173
10 Current CAE Trends in the Automotive Industry 174
10.1 Introduction 175
10.2 The Need for a Fully Digital Development Process 175
10.2.1 Safety 176
10.2.2 Environmental Impact 178
10.2.3 Comfort 179
10.2.4 Method Validation 180
10.3 Digital Methods in the Development Process: State-of-the-Art 180
10.4 Novel Methodologies in Computational Mechanics, Big Data and Artificial Intelligence 183
10.4.1 Reduced Order Modelling 183
10.4.2 Artificial Intelligence and Big Data 183
10.5 Towards a Clever Digital Development Process 184
References 184
11 Establishment of MoS in Chile: Pertinence Assessment Through an Analysis of Previous Scenarios 185
11.1 Introduction 186
11.2 Framework 186
11.3 The Model 188
11.3.1 Objective Functions, Restrictions and the Resolution 189
11.4 The Resolution of the Model 190
11.5 The Results for Preliminary Scenarios 191
11.6 Conclusions 193
References 196
12 Radars in Transport Applications 198
12.1 Introduction 199
12.2 State of Art Manifold Learning 200
12.2.1 Principal Component Analysis 200
12.2.2 Locally Linear Embedding 203
12.3 Geometrical Optics 204
12.3.1 Convergence Results 206
12.3.2 Black-Boxing the Scenario 209
12.4 The Scenario Manifold 211
12.5 Conclusions 213
References 214
13 Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks 215
13.1 Introduction 216
13.2 Materials and Methods 218
13.2.1 Research Data 218
13.2.2 Neural Networks 220
13.2.3 Network Types 223
13.2.4 Scaling Methods 224
13.2.5 Configuration of the Modelled Water Quality Parameters 225
13.2.6 Metrics 227
13.2.7 Learning and Adjusting the Models 227
13.3 Results 230
13.4 Discussion 236
13.5 Conclusion 238
References 239
14 Distortions in Large Aluminum Forgings: Current Situation and Simulation Challenges 241
14.1 Introduction 241
14.2 Distortion in the Aeronautical Industry: An Open Problem 243
14.3 Residual Stresses, Distortion and Reshaping 244
14.4 Post-machining Distortion Mitigation Techniques 246
14.5 Reshaping Simulation: Challenges and Perspectives 247
14.6 Conclusions 250
References 251

Produkt-Details

• Erscheint lt. Verlag: 28.2.2020
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Luft- / Raumfahrttechnik
• ISBN-10: 3-030-37752-0 / 3030377520
• ISBN-13: 978-3-030-37752-6 / 9783030377526