Call for Papers on Advances in Artificial Intelligence for Smart Transportation: Enabling Efficient, Safe, and Sustainable Mobility
In recent years, rapid advancements in artificial intelligence (AI) have led to transformative changes in various domains, and the field of transportation is no exception. The proposed special issue aims to bring together cutting-edge research and developments in the intersection of artificial intelligence and smart transportation systems. The scope of this special issue encompasses a wide range of topics that address challenges and opportunities in creating intelligent, efficient, safe, and sustainable transportation solutions. The integration of AI technologies in smart transportation has the potential to revolutionize the way people and goods move, enhancing mobility while reducing environmental impacts.
Topics of Interest
This special issue will cover a diverse array of topics related to the integration of artificial intelligence in smart transportation systems, including, but not limited to:
- Traffic Management and Optimization: Novel AI techniques for real-time traffic monitoring, congestion detection, dynamic route optimization, and signal control to alleviate traffic congestion and improve overall traffic flow efficiency.
- Autonomous and Connected Vehicles: Advances in AI-driven autonomous vehicle navigation, perception, decision-making, and communication for safer and more reliable self-driving vehicles and cooperative vehicle-to-vehicle/vehicle-to-infrastructure systems.
- Public Transportation Enhancement: AI-powered solutions for enhancing public transportation efficiency, including predictive maintenance of transit systems, demand forecasting, and dynamic scheduling.
- Transportation Infrastructure Maintenance: Utilization of AI for monitoring and maintaining transportation infrastructure, such as bridges, roads, and tunnels, through predictive maintenance and anomaly detection.
- Intelligent Freight and Logistics: AI applications in optimizing freight operations, route planning, last-mile delivery, warehouse management, and supply chain optimization.
- Energy Efficiency and Environmental Impact: AI-driven strategies for reducing the environmental impact of transportation, including electric vehicle charging optimization, emission reduction, and green transportation planning.
- Safety and Security: AI-based approaches to enhance transportation safety through driver behavior analysis, accident prediction, and cybersecurity for connected vehicles and transportation systems.
- Multi-modal Transportation Integration: AI techniques for integrating various modes of transportation, such as public transit, ride-sharing, biking, and walking, to provide seamless and efficient multi-modal journeys.
- Data Analytics and Decision Support: AI-powered data analytics, machine learning, and decision support tools for transportation agencies and policymakers to make informed decisions and formulate effective transportation policies.
Manuscript preparation and submission
Computer Assisted Methods in Engineering and Science (CAMES) is a refereed international journal published quarterly and indexed by Scopus and EBSCO databases.
All manuscripts must be submitted through the journal website: https://cames.ippt.pan.pl/index.php/cames/about/submissions
Submission must be clearly assigned in the system to the “SI on AI for Smart Transportation” section. The publication in this Special Issue is free of charge for the Authors and the published manuscripts will be freely available (open access) for the Readers through the Journal website (https://cames.ippt.pan.pl).
- Full-length paper submission deadline: January 30, 2024
- Notification of the reviewers’ 1st feedback: February 25, 2024
- Submission of revised manuscript: March 25, 2024
- Notification of the re-review: April 25, 2024
- Final notification: May 10, 2024
- Final paper due: May 30, 2024
- Publication: Q3 or Q4 2024
- Mustafa M. Matalgah, Professor, Electrical and Computer Engineering, Professor, General Engineering, University of Mississippi, United States, e-mail: firstname.lastname@example.org & email@example.com
- Sathishkumar Karupusamy, Gobi Arts & Science College, Tamilnadu, India, e-mail: firstname.lastname@example.org / email@example.com
- Professor Akhtar Kalam, BSc, BScEng, MS, PhD, FIET, CEng, FAIE, FIEAust, CPEng, PEV, NER, APEC Engineer, IntPE (Aus), MCIGRE, Life Senior Member of IEEE Professor and Head of External Engagement College of Engineering and Science Victoria University, Melbourne, Australia, e-mail: firstname.lastname@example.org
- Bilal Alhayani, Yildiz Technical University, Istanbul, Turkey, e-mail: email@example.com
- Yu-Chen Hu, Distinguished Professor, Dept. of Computer Science and Information Management, Providence University, Taichung City, Taiwan, Republic of China (ROC), e-mail: firstname.lastname@example.org
Prof. Michał Kleiber – Past ECCOMAS President, Institute of Fundamental Technological Research, Warsaw, Poland
Prof. Tadeusz Burczyński – Chairman of TC on Computational Solids & Structural Mechanics of ECCOMAS, Director of Institute of Fundamental Technological Research, Warsaw, Poland