Sensing Technology in Connected and Automated Vehicles (CAV)
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 37
Special Issue Editors
Interests: intelligent transportation systems; connected and automated vehicle & highway; traffic management and control; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: connected and automated vehicle; AI-driven sensing; vehicle platooning control
Special Issue Information
Dear Colleagues,
With the rapid advancement of intelligent transportation systems (ITSs), connected automated vehicles (CAVs) have emerged as a key solution for enhancing road safety, improving traffic efficiency, and reducing environmental impact. The seamless integration of advanced sensing technologies is fundamental to enabling CAVs to perceive, interpret, and interact with dynamic road environments. These technologies include, but are not limited to, LiDAR, radar, cameras, inertial measurement units (IMUs), vehicle-to-everything (V2X) communication, and sensor fusion techniques.
This Special Issue aims to explore the latest developments in sensing technologies for CAVs, focusing on hardware advancements, perception algorithms, sensor fusion techniques, real-time data processing, and their applications in cooperative driving and decision-making. We invite original research articles, reviews, and case studies that contribute to the advancement of sensing technologies and their role in achieving safe, efficient, and intelligent autonomous mobility.
This Special Issue covers a wide range of topics related to sensing in CAVs, including (but not limited to), the following:
Perception Systems for CAVs:
- LiDAR, radar, camera, and IMU-based sensing;
- Multi-sensor fusion and perception reliability;
- Robust object detection, tracking, and classification;
- Environmental perception under adverse weather conditions.
V2X Communication and Cooperative Perception:
- Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) sensing applications;
- Cooperative perception and collaborative sensing in mixed traffic;
- Edge computing and cloud-based sensor data processing.
Sensing for Autonomous Decision-Making and Control:
- Sensor-based motion planning and trajectory prediction;
- Human-like perception modeling for CAV behavior adaptation;
- Integration of AI and deep learning in sensor data processing.
Challenges and Future Trends in Sensing for CAVs:
- Real-time data processing and low-latency sensing architectures;
- Safety and redundancy in sensor fusion strategies;
- Standardization and interoperability of sensing systems in CAVs.
Dr. Lu Wenqi
Dr. Ziwei Yi
Dr. Yikang Rui
Guest Editors
Manuscript Submission Information
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Keywords
- connected automated vehicles
- advanced sensing technologies
- V2X communication and cooperative perception
- autonomous decision-making and control
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