Sensor Fusion for the Safety of Automated Driving Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 30 May 2025 | Viewed by 4277
Special Issue Editors
Interests: authentication; automated driving security; mobile security
Interests: software security; network security
Special Issues, Collections and Topics in MDPI journals
Interests: program security; threat detection; AI security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The large-scale deployment of autonomous vehicles has been continually delayed due to safety concerns. To enhance the safety of automated driving systems, sensor fusion plays a crucial role in integrating data from various sensors like cameras, LiDAR, radar, ultrasonic, GPS, and IMUs. By combining information from these sensors, automated vehicles can have a more comprehensive understanding of their surroundings, enabling better decision-making and improving overall system reliability. Sensor fusion helps in accurately detecting objects, predicting their movements, and ensuring the vehicle operates safely in diverse driving conditions.
This Special Issue was conceived to further the state-of-the-art in sensor fusion architecture, technology, and algorithms for autonomous driving to achieve safety, robustness, and efficiency in autonomous vehicles. In recent years, sensor fusion technology has made great progress and promoted the development of safety and reliability in autonomous driving. However, these technologies have strict autonomous driving system hardware and software requirements, which inevitably increases the complexity of the systems. To this end, we welcome submissions of various advanced multi-sensor fusion approaches for perception tasks such as object detection, semantic segmentation, object classification, depth completion, and prediction, which can be used to improve the safety and robustness of autonomous driving systems while keeping costs as controllable as possible.
Dr. Man Zhou
Dr. Weina Niu
Dr. Xin Liu
Guest Editors
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Keywords
- autonomous driving
- safety and robustness
- autonomous driving system security
- sensor data security
- sensor fusion architecture
- cameras
- LiDAR
- radar
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