Machine Learning for Secure and Efficient Connected and Autonomous Vehicles
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 29
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; computer vision
Special Issue Information
Dear Colleagues,
Connected and autonomous vehicles (CAVs) are transforming intelligent transportation systems by integrating automation, connectivity, and machine learning (ML). Advanced sensor networks, along with diverse communication modes, facilitate real-time information exchange which is essential for safe navigation and route planning. By reducing congestion and fuel consumption, CAVs can ultimately foster eco-friendly urban mobility and resilient transportation infrastructures that support sustainable development goals.
This Special Issue aims at gathering state-of-the-art ML models and methodologies tailored for improving the security, integrity, and overall performance of CAV systems. The Guest Editors welcome contributions that address challenges in data-driven sensor fusion, real-time decision-making, and robust communication protocols, while also focusing on optimizing perception, localization, planning, and control mechanisms.
Considering the recent advancements and emerging challenges in integrating ML for secure, efficient, and sustainable CAV systems, the Guest Editors invite submissions of state-of-the-art research articles on sustainable intelligent transportation. The topics of interest include, but are not limited to, the following:
- Energy-efficient autonomous mobility using ML;
- Real-time decision-making by reinforcement learning;
- Deep learning for scene perception;
- Optimized vehicle-to-everything (V2X) communications for CAVs;
- Prediction, control, and decision-making through ML;
- Integrating human perception–action into CAVs;
- Robust ML models against adversarial attacks;
- Sensor fusion for enhanced perception.
Dr. Soodeh Nikan
Dr. Hossein Hassani
Guest Editors
Manuscript Submission Information
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Keywords
- intelligent transportation systems
- connected and autonomous vehicles
- sustainable transportation
- vehicular networks
- machine learning
- sensor fusion
- traffic efficiency
- autonomous driving
- perception and localization
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