AI Applications in Transportation and Logistics

Dear Colleagues,

As transportation systems and global supply chains grow more complex, dynamic, and digitalized, artificial intelligence (AI) emerges as a powerful tool to optimize operations, predict disruptions, and enhance decision-making across strategic, tactical, and operational levels. At its core, AI represents a shift from reactive problem-solving to proactive, intelligent systems that learn, adapt, and optimize. It embodies the belief that efficiency, sustainability, and resilience in transportation and logistics are not just human challenges but can be augmented, or even redefined, by machine intelligence. AI does not merely automate tasks; it introduces a new paradigm where data becomes insight, patterns reveal opportunities, and networks self-adjust to dynamic conditions. By integrating predictive analytics with IoT and big data, these AI-driven systems create more adaptive, fast, and cost-effective transportation and logistics systems capable of meeting the demands of Industry 5.0. AI in this field reflects a deeper aspiration: to harmonize technological and human interactions with the fluidity of real-world movement. It is not just about faster deliveries or smoother traffic, it is about reshaping connectivity itself, where systems think, adapt, and evolve alongside the societies they serve. By compiling original research and review articles, this Special Issue serves as a vital resource for practitioners, planners, and researchers seeking data-driven, AI-enhanced solutions to transform transportation and logistics systems into more adaptive and future-ready ones.

 Research topics on AI Applications in Transportation and Logistics include, but are not limited to, the following:

• System Optimization: AI-driven approaches for improving transportation and logistics systems design and operations.
• Performance Prediction: Machine learning for forecasting system behavior under varying conditions.
• Policy and Scenario Testing: Evaluating transport policies and conducting what-if analyses for better decision-making.
• Traffic and Congestion Management: AI-based solutions for analyzing and mitigating traffic flow disruptions.
• Freight and Logistics: Intelligent routing, supply chain optimization, and automation in cargo movement.
• Risk and Safety: AI applications in disruption management, accident prevention, and system reliability.
• Emerging Technologies: Digital twins, IoT, and agent-based modeling for smarter transportation networks.
• Autonomous Vehicles: Assessing their influence on traffic dynamics and control strategies.
• Sustainability: Environmental impact assessments and green logistics powered by AI.

Prof. Dr. Eugen Rosca
Prof. Dr. Radovan Madleňák
Prof. Dr. Florin Valentin Rusca
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• AI-powered transport and traffic management
• smart logistics optimization
• machine learning for predictive modeling and forecasting
• AI and autonomous vehicles
• digital twin for supply chains
• sustainable logistics with AI
• AI for risks and accident prevention
• human-AI collaboration in logistics