Intelligent Control Systems for Autonomous Vehicles
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 10 February 2025 | Viewed by 3325
Special Issue Editors
Interests: model predictive control; reinforcement learning; connected and automated vehicles; electric vehicles; renewable energy systems
Special Issues, Collections and Topics in MDPI journals
Interests: systems science and control theory with emphasis on vehicle health management using vehicle dynamics theory and machine learning algorithms; resilient control of autonomous vehicles
Special Issue Information
Dear Colleagues,
As autonomous vehicles continue to revolutionize the transportation landscape, this Special Issue aims to showcase innovative research at the intersection of sensor technologies and intelligent control systems. We invite researchers, engineers and experts to contribute their latest findings and methodologies that enhance the intelligence and autonomy of vehicles. Topics of interest include sensor fusion, machine learning algorithms, real-time decision-making and planning, human–machine interactions and robust control strategies. By delving into these crucial aspects, we seek to address the challenges and opportunities in developing intelligent control solutions that pave the way for safer, more efficient and reliable autonomous transportation.
This Special Issue provides a platform for interdisciplinary discussions and fosters collaboration between researchers in sensor technology and control systems. We anticipate that the collected submissions will significantly contribute to the ongoing dialogue on shaping the future of autonomous vehicles. Submissions are welcome from researchers worldwide who are at the forefront of this transformative field.
Topics include, but not limited to:
- Autonomous vehicles;
- Intelligent control;
- Sensor fusion;
- Machine learning-based vehicle sensor and control;
- Real-time decision-making and planning;
- Robust control;
- Human–machine interaction;
- Predictive control;
- Sensor technologies;
- Autonomous systems.
Dr. Jun Chen
Dr. Wen-Chiao Lin
Guest Editors
Manuscript Submission Information
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Keywords
- autonomous vehicles
- human–machine interaction
- sensor fusion
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Integrated Decision and Motion Planning for Highway with Multi-objects by Naturalistic Driving Study
Authors: Feng Gao, Guanglun Zhan , Xu Zheng and Jie Ma
Affiliation: College of Mechinal and Vehicle Engineering, Chongqing University
Abstract: With the increasement of intelligent level, it becomes a trend that more and more modules of au-tomatic driving system should be combined together to realize better performance and adaptability by reducing information loss. In this study, considering the fact that the human driving decision is influenced by the number of surrounding objects, which is derived by naturalistic driving study, an integrated decision and motion planning system is designed for highway with multi-objects. A two-layer structure is presented to decouple the influence of traffic environment and dynamical control of ego-vehicle by the cognitive safety area, whose size is determined by the naturalistic driving behavior. The artificial potential field method is used to comprehensively describe the in-fluence of all objects on the cognitive safety area, whose lateral motion dynamics is determined by the attention mechanism of human driver during lane change. Then the interaction among the designed cognitive safety area and the ego-vehicle can be simplified to a spring damping system and the desired dynamical states of ego-vehicle can be obtained analytically for better computation ef-ficiency. The effectiveness has been validated by several comparative tests under complicated scenarios with multi-vehicles.
