Buch, Englisch, 464 Seiten
Buch, Englisch, 464 Seiten
ISBN: 978-1-394-35106-0
Verlag: John Wiley & Sons Inc
Exploration of how cutting-edge digital technologies can power humanity’s collective efforts towards urban transport environmental sustainability
Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation delves into the nexus between urbanization, transportation, and climate change, providing a comprehensive analysis of how traditional transportation systems contribute to greenhouse gas emissions and air pollution, thereby undermining our collective efforts towards environmental sustainability. Through lucid explanations and real-world examples, the book explores how cutting-edge digital technologies, including Artificial Intelligence (AI), the Internet of Things (IoT), and blockchain, can revolutionize urban transportation. Readers will gain insights into the role of AI-powered platforms and management software solutions that optimize energy usage, enhance efficiency, and promote sustainable mobility.
With contributions for a variety of experts in the fields of transportation, environmental science, and artificial intelligence, this book delivers perspectives on topics including: - Intelligent traffic management and the impact of computer vision in smart transportation
- Connected lighting and AI-empowered battery management systems
- Edge computing and edge AI for real-time insights
- Route optimization and navigation, smart parking solutions, and fleet and fuel optimization
- Implementation of smart microgrids and renewable energy sources such as solar and wind
Whether you are a policymaker, urban planner, transportation professional, or simply a concerned citizen, Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation serves as a vital resource for understanding the challenges and opportunities in transitioning towards a more sustainable future in the field of urban transportation.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
List of Contributors xxi
About the Editors xxvii
1 Recent Trends in Intelligent Transportation Systems 1
Kathi Durgesh, Siddharth Garia, and Vishal Kumar Narnoli
1.1 Introduction 1
1.2 Methodology 3
1.3 Results 9
1.4 Discussion 10
2 Artificial Intelligence and IoT Applications Transforming the Automotive Industry 15
Raviprakash R Salagame
2.1 Introduction 15
2.2 Automotive AI Applications and Urban Use Cases 23
2.3 Connected Vehicles 30
2.4 Electric Vehicles (EV) 32
2.5 Shared Mobility 35
2.6 Future Trends Toward Smart Transportation 35
2.7 Conclusion 36
3 Artificial Intelligence in Transportation Using Automated Grading, Adaptive Learning, and Predictive Maintenance to Increase Efficiency 41
S. Cyciliya Pearline Christy, K. Merriliance, and Mary Immaculate Sheela Lourdusamy
3.1 Introduction 41
3.2 Overview of Artificial Intelligence in Transportation 42
3.3 Automated Grading Systems in Transportation 44
3.4 Adaptive Learning in Traffic Management and Logistics 46
3.5 Predictive Maintenance in Transportation Systems 48
3.6 Ethical, Regulatory, and Security Considerations 50
3.7 Future Outlook and Emerging Technologies 51
3.8 Conclusion 53
4 Autonomous Vehicles and Smart Mobility 57
P. Sudheer, S. Ashmad, M. Saravanan, and A. Immanuel
4.1 Introduction 57
4.2 Challenges in Smart Mobility and Autonomous Vehicles 62
4.3 Case Studies and Practical Applications of Smart Mobility and Self-driving Cars 64
4.4 Policies, Ethics, and Governance in the Autonomous Vehicle Ecosystem 66
5 Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation 73
Ishika Gupta, Hriday Gupta, Siddharth Gupta, and Prerna Ajmani
5.1 Introduction 73
5.2 Background 74
5.3 Enabling Technologies 78
5.4 Components 84
5.5 AI-driven Sustainable Solutions 92
5.6 Security and Privacy in AI and IoT for Smart Cities and Electric Vehicles 95
5.7 Case Studies and Real-world Implementations 100
5.8 Challenges for 6G 105
5.9 Future Directions 106
5.10 Conclusion 110
6 Smart Mobility: Integrating AI for Sustainable Urban Transportation Solutions 113
A. Jothi Kumar
6.1 Introduction 113
6.2 AI in Traffic Management Systems 114
6.3 Virtual Architecture for AI-based Traffic Management Systems 117
6.4 AI Applications in Sustainable Urban Mobility 119
6.5 Data-driven Mobility Solution 121
6.6 Case Studies of AI Implementation in Smart Cities 121
6.7 Moral and Political Views 121
6.8 Future Trends and Innovations 122
6.9 Conclusion 123
7 Reinforcement Learning for Energy-efficient Urban Freight Transportation 125
Nancy Jasmine Goldena and R. Rashia Subashree
7.1 Introduction 125
7.2 Fundamentals of RL 126
7.3 RL Applications in Energy-efficient Urban Freight Transportation 127
7.4 Integration of RL Applications with Smart Logistics and IoT 131
7.5 Challenges and Limitations 136
7.6 Future Directions 137
7.7 Conclusion 138
8 Advancements and Challenges in Autonomous Vehicles and Smart Mobility: The Role of AI in Transforming Transportation 141
A. Jane, Dr. K. Merriliance, and Dr. Mary Immaculate Sheela Lourdusamy
8.1 Introduction 141
8.2 Advancements in Autonomous Vehicles and Smart Mobility 144
8.3 Artificial Intelligence in Autonomous Vehicles 145
8.4 Perception and Fusion of Sensors for AI-powered Automobiles 148
8.5 Advantages of AI in Autonomous Vehicles 150
8.6 Challenges in Autonomous Vehicles and Smart Mobility 151
8.7 Future Directions and Conclusion 152
9 Enhancing Urban Traffic Management with Multi-scale Hierarchical GANs 159
Ashik Shah Jahangeer and P Shanmugavadivu
9.1 A System Stuck in Time 159
9.2 When GANs Hit the Road: The Gaps in Current AI Models 162
9.3 Reimagining Intelligence: The Architecture of MSH-GAN 164
9.4 The City in Layers: Micro and Macro-level Generators 167
9.5 Listening to the City: Real-time IoT Data Integration 169
9.6 Understanding the Why: Hierarchical Modeling and Contextual Awareness 172
9.7 Thinking at the Edge: Decentralized Computation for Faster Response 174
9.8 Measuring Intelligence: Evaluating the Performance of MSH-GAN 176
9.9 From Control to Care: MSH-GAN and the Future of Smart Cities 179
9.10 Looking Ahead: The Road Beyond MSH-GAN 182
10 IoT and AI Integration in Traffic Management 187
J. Steffi, K. Merriliance, and Mary Immaculate Sheela Lourdusamy
10.1 Introduction 187
10.2 Role of IoT in Traffic Management 188
10.3 AI Applications in Traffic Optimization 191
10.4 Smart Traffic Signals and AI-driven Control Systems 193
10.5 Incident Detection and Emergency Response 195
10.6 Public Transport Enhancement with IoT and AI 196
10.7 Environmental and Sustainability Benefits 198
10.8 Challenges and Future Trends 200
11 Intelligent Urbanism: AI and Big Data-driven Approaches to Planning, Design, and Transportation 205
R. Saradha
11.1 Introduction 205
11.2 Literature Background 207
11.3 Methodology 210
11.4 Results and Discussion 221
11.5 Conclusion 223
12 AI-driven Public Transport Solutions 231
Shantanu Bindewari, Prakhar Consul, Hilal Ahmed Shah, Basab Nath, and Mansi Trivedi
12.1 Introduction 231
12.2 AI Applications in Transportation 234
12.3 Introduction to AI in Automation and Ticketing 237
12.4 AI for Safety and Security 241
12.5 Dynamic Route Optimization Systems 243
12.6 AI in Public vs. Private Transportation 245
12.7 Challenges and Ethical Considerations 249
12.8 Future Trends and Innovations 250
12.9 Conclusion 251
13 AI-driven Data Analytics for Smart Urban Transport: Innovations, Challenges, and Future Trends 255
A. Jasmine Sugil, K. Merriliance, and Mary Immaculate Sheela Lourdusamy
13.1 Introduction 255
13.2 AI-powered Data Sources in Urban Transport 260
13.3 AI Techniques for Urban Transport Analytics 266
13.4 Key Applications of AI in Urban Transport 270
13.5 Case Studies and Real-world Implementations 272
13.6 Challenges and Ethical Considerations 275
13.7 Future Trends in AI for Urban Transport 277
13.8 Conclusion 280
14 Transforming Smart Mobility: L4S and NaaS APIs for Real-time Traffic Management and Autonomous Transport 283
L. Ameer Shohail
14.1 Introduction 283
14.2 Architectural Foundation for Real-time and Autonomous Mobility 284
14.3 Current Directions in Programmable Transport Networks and LatencyControl 288
14.4 System Design and Implementation Strategy for Real-time Mobility Control 291
14.5 Results from Real-time Policy and Queue Enforcement 293
14.6 Reflections on Programmable Responsiveness in Urban Mobility 296
14.7 Conclusion 298
15 AI-driven Public Transportation: Enhancing Efficiency, Sustainability, and User Experience 301
M. Robinson Joel
15.1 Introduction 301
15.2 Existing AI Uses in Public Transportation 304
15.3 Recognizing AI's Significance in Transportation 305
15.4 AI Applications in Transportation: Exemplary Instances 307
15.5 Traffic Management Systems Using AI 309
15.6 Top AI Resources for Public Transportation 310
15.7 AI Improve Public Transportation Efficiency 318
15.8 Safety Benefits of AI in Public Transportation 319
15.9 Flowchart for GPS-based Vehicle Tracking 321
15.10 Build Your Own ESP32 GPS Tracker with Live Tracking 324
15.11 Market Share of AI in Transportation by Different Elements 326
15.12 Related Work 331
15.13 Conclusion 336
16 Cognitive AI for Adaptive and Resilient Urban Transportation: A Data-driven Approach to Sustainable Mobility 343
Vishal Jain, Archan Mitra, and Sanchita Paul
16.1 Introduction 343
16.2 Conceptual Framework and Literature Review 346
16.3 Methodology 350
16.4 Integrated Cognitive AI Framework for Urban Transportation 352
16.5 Data Analysis and Empirical Findings 355
16.6 Discussion 358
16.7 Conclusion 361
17 Optimizing Urban Traffic with Graph Analytics: A Case Study of a Metropolitan Transportation Network 367
S. Rakshika and Sudeepa Roy Dey
17.1 Introduction 367
17.2 Related Work 370
17.3 Types of Routing Algorithm 372
17.4 Work 375
18 Urban Mobility Reimagined: AMRUT Interventions and the 2041 Outlook 387
S. Thangapriya, Nancy Jasmine Goldena, T. S. Vasughi, M. Kannan, and Barath Ramesh
18.1 Introduction 387
18.2 Geospatial Mapping of Tirunelveli Using Advanced Technologies 388
18.3 Identifying Research Gaps in Tirunelveli for Sustainable Regional Development 389
18.4 Climate and Rainfall 391
18.5 Precipitation 392
18.6 Soil Type Analysis and Resource-efficient Agricultural Planning in Tirunelveli Region 393
18.7 Geomorphology 394
18.8 A Road map for Tirunelveli's Future Economy 397
18.9 AI-based Urban Housing Analytics and Slum Rehabilitation Forecasting for Tirunelveli LPA 398
18.10 Tirunelveli 2041 as a Sustainable Growth Use Case 399
18.11 Conclusion 403
19 GIS-based Analysis of Road Accidents: A Case Study on Hotspot Identification and Safety Improvement 407
Kirti Goyal, Siddharth Garia, Anoop Bhardwaj, Amol Sharma, Sneha Das, and Animesh Nayak
19.1 Introduction 407
19.2 Methodology 408
19.3 Results and Discussion 408
19.4 Data Collection and Preparation 408
19.5 Analysis 412
19.6 Identifying Blackspots Using GIS 414
19.7 Key Insights 416
19.8 Conclusion 417
19.9 Recommendations 417
19.10 Way Forward 417
References 418
Index 421
