Call for papers: SAE International Journal of Connected and Automated Vehicles
Special Issue on Machine Learning and Deep Learning Techniques for Connected and Autonomous Vehicle Applications
The increasing scale of data, computational power, and associated algorithmic innovations are the main drivers for the progress we see in the field of machine learning (ML) and deep learning (DL). These developments have a huge potential for the automotive industry. This Special Issue aims to cover the most recent advances in the usage of ML-DL techniques in the context of next-generation connected and autonomous vehicles (CAVs). The SAE International Journal of Connected and Automated Vehicles and this special issue provide a peer-reviewed platform for both industry and academia to present new research and developments in this important area.
Topics of interest include, but are not limited to:
- Real-time embedded ML-DL applications in vehicular CAN/LIN/Ethernet networks.
- Software and hardware requirements for the successful deployment of embedded ML-DL solutions for CAVs.
- ML-DL based virtual sensing and sensor fusion algorithms for vehicle dynamics applications in CAVs.
- Automated driving (e.g. end-to-end learning).
- Vehicle predictive maintenance/diagnostics using advanced ML algorithms.
- New mobility concepts powered by ML-DL.
- Virtual testing of ML-DL algorithms in CAV applications.
- Novel ML-DL algorithms for deployment on hardware with limited memory.
- Data-driven product development for CAVs.
- Artificial Intelligence (AI) for CAVs.
- Application of AI for delivering an enriched in-car experience.