Innovation of CAV: Advanced Technology and Sustainable Applications
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 1 June 2026 | Viewed by 398
Special Issue Editors
Interests: traffic big data; cooperative vehicle infrastructure system; intelligent transportation system; traffic flow and autonomous driving
Special Issues, Collections and Topics in MDPI journals
Interests: traffic flow theory; connected and automated vehicles; intelligent transportation systems
Special Issues, Collections and Topics in MDPI journals
Interests: traffic signal control; connected automated vehicles; traffic flow theory; traffic simulation; machine learning; trajectory predictions
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Driven by the development of smart cities, building a safe, efficient, low-carbon, and sustainable transportation system has become a major global goal. As a key component of future mobility systems, Connected and Autonomous Vehicles (CAVs) play a central role in promoting the transformation and upgrading of modern transportation. Their capabilities in perception, decision-making, and control under complex traffic environments are increasingly crucial for the implementation of autonomous driving technologies. This special issue focuses on the latest advances in core CAV technologies, including intelligent perception, decision-making and control algorithms driven by data or models, aiming to enhance the stability and safety of CAVs in real-world scenarios and support the development of greener and more efficient urban transportation systems.
At the same time, the integration of cutting-edge technologies such as artificial intelligence (AI) and large language models (LLM) is providing strong momentum for the intelligent evolution of CAVs. These technologies not only accelerate the deployment of CAVs in shared mobility and multimodal transportation systems, but also demonstrate significant advantages in improving traffic efficiency, optimizing resource allocation, and reducing carbon emissions. This special issue welcomes high-quality research contributions with both theoretical depth and practical value in areas such as AI- and LLM-enabled CAV technologies, the integration of CAVs into urban transportation systems, and technological innovations aimed at achieving sustainable mobility. Topics of interest include, but are not limited to:
- CAV perception algorithms based on multi-source data fusion
- Efficient and lightweight perception mechanisms for CAVs
- Data or Model-driven decision-making and control algorithms for CAVs
- Decision-making and trajectory planning of CAVs in mixed traffic environments
- Optimization of roadside units involving both connected and non-connected vehicles
- Vehicle platooning with collaborative CAV control
- Cooperation and game-theoretic modeling between connected and non-connected vehicles
- Stability analysis and optimization of complex mixed traffic flows
- Applications of AI in CAV systems
- Innovative applications of LLM in CAVs
- CAV integration into multimodal transportation systems
- Intelligent scheduling and system optimization of shared CAVs
- Impacts of shared CAVs on urban traffic efficiency and sustainability
Dr. Jiandong Zhao
Dr. Yanyan Qin
Dr. Zhihong Yao
Guest Editors
Manuscript Submission Information
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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.
Keywords
- connected and automated vehicle
- environmental perception
- decision making and control
- artificial intelligence
- large language model
- shared CAV
- multimodal transportation
- sustainable traffic
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