Sustainable Autonomous Driving Systems
This special issue belongs to the section "Sustainable Transportation".
Special Issue Information
Dear Colleagues,
The development of sustainable autonomous driving systems is a critical research area, given the increasing demand for efficient, eco-friendly, and safe transportation. Autonomous driving is an emerging field that requires complex and efficient algorithms to process sensor data and make decisions in real time. One of the main challenges in this field is designing sustainable and light-weight models that can run on resource-constrained devices, such as embedded systems or low-power processors, while still achieving high accuracy and robustness. This Special Issue on Sustainable Autonomous Driving Systems focuses on the latest developments, challenges, and opportunities in this field. The Issue features articles that cover various aspects of sustainable autonomous driving systems, including the latest computer vision and machine learning algorithms, such as network architecture design, network architecture search, light-weight model design on image/BEV/point-cloud perception algorithms, and other autonomous-driving-related topics. This Special Issue highlights the importance of sustainable technology in reducing the environmental impact of transportation and promoting sustainable development in the field of autonomous driving.
Dr. Guangliang Cheng
Dr. Ting-Bing Xu
Dr. Xiangtai Li
Guest Editors
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Keywords
- sustainable model design
- light-weight model design
- network architecture search
- model compression/distillation/quantization
- transfer learning and domain adaptation
- real-time image/point-cloud object detection
- real-time image/point-cloud understanding
- smart vehicle-to-vehicle communication system
- other sustainable-autonomous-driving-related topics
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Published Papers
Sustainability - ISSN 2071-1050