Sensors in Intelligent Vehicle Dynamics and Control
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 30 May 2026 | Viewed by 215
Special Issue Editors
Interests: advanced sensor technology; intelligent vehicle dynamics analysis and control; intelligent tires
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent vehicle control; intelligent tires
Interests: vehicle dynamics analysis and control; tire model
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent tire technology
Interests: intelligent vehicles; intelligent tire technology
Interests: vehicle test; tire model
Special Issue Information
Dear Colleagues,
Intelligent vehicle dynamics and control rely heavily on advanced sensor technologies to enhance safety, efficiency, and autonomous driving capabilities. Sensors play a crucial role in monitoring vehicle states, environmental conditions, and driver inputs, enabling real-time decision-making for stability control, traction management, and collision avoidance. Key sensors such as inertial measurement units (IMUs), wheel speed sensors, LiDAR, radar, and vision-based systems provide critical data on vehicle motion, road conditions, and surrounding obstacles. By integrating these sensors with advanced control algorithms, modern vehicles can adapt to dynamic driving scenarios, optimize performance, and ensure passenger comfort. Furthermore, the fusion of multi-sensor data improves system reliability and robustness, supporting the development of autonomous driving systems. This field continues to evolve with advancements in sensor accuracy, miniaturization, and AI-driven processing, paving the way for next-generation intelligent transportation systems.
Dr. Bo Li
Prof. Dr. Shaoyi Bei
Dr. Fen Lin
Dr. Haichao Zhou
Prof. Dr. Nan Xu
Prof. Dr. Xiaolong Zhang
Guest Editors
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Keywords
- vehicle dynamics
- sensor fusion
- inertial measurement unit (IMU)
- LiDAR and radar
- autonomous driving
- stability control
- real-time monitoring
- intelligent transportation systems
- environmental perception
- adaptive control algorithms
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