Aim and Scope
The Journal of Transportation Analytics aims to advance knowledge and practice in transportation systems through the application of data-driven, analytical, and computational methodologies. The journal focuses on the development and application of innovative approaches that enhance decision-making, efficiency, sustainability, and resilience in transportation and mobility systems.
The scope of the journal encompasses both theoretical and applied research that integrates transportation science with methodologies from operations research, data analytics, artificial intelligence, machine learning, and statistics. The journal encourages interdisciplinary contributions addressing a wide range of topics, including but not limited to:
Transportation analytics and data-driven modeling
Optimization and simulation of transportation systems
Intelligent transportation systems and smart mobility
Urban transportation planning and traffic analysis
Freight transportation, logistics, and supply chain analytics
Sustainable and green transportation systems
Mobility-as-a-Service (MaaS) and emerging mobility solutions
Big data and AI applications in transportation
Transportation network design and resilience analysis
Demand forecasting and behavioral modeling in transport systems
The journal particularly welcomes studies that demonstrate methodological innovation, real-world applicability, and measurable impact on transportation systems. Contributions that bridge the gap between theory and practice, or that provide actionable insights for policymakers and industry stakeholders, are strongly encouraged.
