Intelligent Urban Mobility: Decision Support Systems for Sustainable Transportation explores the role of technology in enabling greener, more accessible transportation in cities worldwide. This book provides insights into leveraging decision support systems to drive positive change by focusing on applied soft computing techniques, artificial intelligence, and algorithms for fuzzy systems. Researchers and professionals will find actionable information on mitigating congestion and emissions through sustainable mobility initiatives, which bridges the gap between theory and real-world practice.
The book also offers technical guidance and expert perspectives on the application of decision support systems to evaluate and optimize planning for sustainable transit options. The book highlights innovative models and frameworks for analyzing mobility options and planning sustainable transport systems. It is an essential resource for researchers, graduate students, and professionals in transportation, urban planning, civil engineering, and decision sciences who aim to redesign city transportation to reduce environmental impact and carbon emissions.
1. Sustainable Urban Mobility Plans (SUMPs) An Overview
2. Leveraging Meta-Heuristics and Deep Learning for Decision Support Systems
in Sustainable Transport Applications
3. Consensus Reaching Process for Intelligent Vehicle Group Decision-Making
in Smart Transportation System
4. Shared Electric Vehicle Usage Risk Prioritization Based on Integrated FMEA
and CRADIS Methods with T-Spherical Uncertain Linguistic Information
5. Safety Risk Assessment of Autonomous Vehicles for Sustainable
Transportation
6. Developing a GIS-Supported SVN-WENSLO-ARLON Hybrid Method for Bicycle
Pooling Location Selection: A Case Study in Turkiye
7. Identifying Effective Risk Management Policies for Sustainable Urban
Transportation Projects
8. Flexible Linguistic Consensus Decision Making for Sustainable Transport
Practices
9. Optimization based decision making for sustainable transport: Insights
into the aviation industry
10. A Generalized Hellinger Distance-Based Spherical Fuzzy TOPSIS Method for
Sustainable Transport Systems Selection
11. Fuzzy multi-criteria decision making for assessing public transportation
systems for sustainable transportation
12. Determining enablers for the application of sustainable and resilient
urban transport systems using T-spherical fuzzy DEMATEL-ISM model
13. Selection of the solution for the integration of sustainable and
resilient urban transport systems using linguistic T-spherical fuzzy COCOSOB
method
14. Sustainable AI-Assisted Energy-Efficient Edge Cloud System for Industrial
Internet of Things Applications
Dr. Muhammet Deveci is an Associate Professor at the Department of Industrial Engineering in the Turkish Naval Academy, National Defense University, Istanbul, Turkey, and he is Honorary Senior Research Fellow with the Bartlett School of Sustainable Construction, University College London, UK. Dr. Deveci is also a Visiting Professor at Royal School of Mines in the Imperial College London, London, UK. He worked as a Visiting Researcher and Postdoctoral Researcher, in 2014-2015 and 20182019, respectively, with the School of Computer Science, University of Nottingham, Nottingham, U.K. Dr Deveci is an outstanding researcher and has published over 240 papers in journals, as well as more than 25 contributions in International Conferences related to his areas. Dr. Deveci received the 100th-anniversary award for his worldwide scientific achievements from the Scientific and Technological Research Council of Turkey (TUBITAK).
Dr Deveci has also been engaged with the wider community providing academic service through chairing/organising conferences, streams, tutorials, reviewing papers, and acting as Editorial Board Member of journals including IEEE Transactions on Intelligent Vehicles (T-IV), IEEE Transactions on Emerging Topics in Computational Intelligence, Information Sciences, Applied Soft Computing, Engineering Applications of Artificial Intelligence, and Artificial Intelligence Review.
Dr Deveci is an internationally recognized scientist in intelligent decision support systems underpinned by computational intelligence, particularly uncertainty handling, fuzzy systems, combinatorial optimization, and multicriteria decision making. His research and development activities are multidisciplinary and lie at the interface of operational research, computer science and artificial intelligence. He has been tackling challenging real-world problems without stripping off their complexities, including climate change, renewable energy, sustainable transport, and urban mobility.
