End-to-End Autonomous Driving
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 250
Special Issue Editors
Interests: autonomous vehicles
Special Issue Information
Dear Colleagues,
In the past decade, with the continuous development of deep learning technology and its in-depth application in the field of autonomous driving, the performance of autonomous driving algorithms has been greatly improved. In the process of the development of autonomous driving technology, technologies such as vehicle-to-everything, HD maps, and modular pipeline have emerged. However, these technologies have disadvantages such as high implementation costs, high maintenance costs, and performance degeneration in complex scenarios. As algorithms develop in the direction of simplification and embodiment, end-to-end models have become the mainstream of current research, and their performance has been greatly improved compared to previous technologies, allowing people to see the dawn of large-scale applications of autonomous driving technology.
This Special Issue aims to promote the development of end-to-end autonomous driving theory and technology.
This Special Issue will accept research work on topics related to end-to-end autonomous driving, including but not limited to the following topics:
1. End-to-End Path Planning;
2. Motion Control;
3. Environment Perception;
4. Simulation;
5. Datasets;
6. Evaluation Method.
Dr. Haichuan Li
Dr. Shizheng Wang
Guest Editors
Manuscript Submission Information
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Keywords
- autonomous driving
- deep learning
- transformer
- path planning
- motion control
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