Data-Driven Urban Mobility: Modeling, Optimization, and Intelligent Transportation Systems
A special issue of Urban Science (ISSN 2413-8851). This special issue belongs to the section "Urban Mobility and Transportation".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 153
Special Issue Editors
Interests: intelligent transport systems; smart mobility; multimodal transport analysis; machine learning in transport; transport mode detection; GPS trajectory analysis
Interests: transport optimization; operations research in transportation; green logistics; urban mobility; data-driven transport analysis; intelligent transportation systems; vehicle routing and scheduling
Special Issue Information
Dear Colleagues,
Rapid urbanization, increasing travel demand, and the growing availability of large-scale mobility data are transforming the way cities understand and manage transportation systems. Consequently, this Special Issue focuses on recent advances in mobility modeling, urban computing, optimization methods, and intelligent transportation systems (ITSs), highlighting innovative approaches that leverage data driven methods, computational models, and advanced optimization techniques to improve urban mobility. The aim is to bring together interdisciplinary research that integrates transportation science, operations research, data analytics, artificial intelligence, insurance analytics, and urban planning to address complex mobility challenges in contemporary cities.
The scope of the Special Issue includes, but is not limited to, mobility pattern analysis, travel demand modeling, multimodal transportation systems, optimization models for transport planning and operations, smart infrastructure, and traffic prediction and management. Particular attention will be given to optimization-based approaches for traffic management, public transport scheduling, network design, and mobility service operations. This Special Issue also encourages research on emerging mobility-related risk assessment frameworks, including insurance models based on mobility data such as usage-based insurance (UBI), telematics-driven risk modeling, and data-informed insurance policy design. Contributions exploring new data sources—such as mobile phone data, GPS trajectories, sensor networks, connected vehicle data, and telematics—are especially encouraged.
By combining perspectives from urban computing, optimization modeling, intelligent transportation systems, and mobility-related risk analytics, this Special Issue aims to provide new methodological frameworks and empirical insights for understanding and managing mobility in rapidly evolving urban environments. It seeks to complement the existing literature by emphasizing integrated, data-intensive, and optimization-driven approaches that bridge theoretical modeling with practical applications in transport management, mobility services, and insurance policy design, ultimately supporting safer, more efficient, and sustainable transportation systems.
Dr. Martina Erdelić
Dr. Tomislav Erdelić
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Urban Science is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- urban mobility
- mobility modeling
- optimization models
- urban computing
- intelligent transportation systems
- usage-based insurance
- telematics
- traffic prediction
- multimodal transport
- smart cities
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