Advancements in Motion Planning and Control for Autonomous Vehicles
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: closed (20 July 2025) | Viewed by 555
Special Issue Editors
Interests: motion planning; computational optimal control; machine learning; energy management
Interests: motion planning; computational optimal control; numerical optimization
Special Issues, Collections and Topics in MDPI journals
Interests: energy management; numerical simulation; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Autonomous vehicles are increasingly tasked with performing complex operations in dynamic and uncertain environments. The effective functioning of these systems relies on the seamless integration of motion planning and control modules, which enable safe, efficient, and reliable autonomous behavior. When optimally designed, these modules account for a diverse range of real-world variables and can be fine-tuned to achieve performance goals, such as energy efficiency, reduced operational time, user comfort, and minimization of wear on system components.
This Special Issue invites high-quality contributions that explore cutting-edge advancements in the design, implementation, and evaluation of motion planning and control methodologies. We welcome innovative approaches that address data-driven methods, which partially or entirely replace conventional autonomous software pipelines, as well as control strategies for systems within autonomous vehicles that cooperate with motion planning and control. Submissions presenting promising methodologies, supported by robust experimental validation or demonstrating potential for near-term real-world applications, will be given particular consideration.
Topics of particular interest include, but are not limited to, the following:
- Path, trajectory, and motion planning;
- Path, trajectory, and motion control;
- Simulation and validation of motion planning and control;
- Real-world applications of motion planning and control;
- End-to-end learning for autonomous vehicles;
- Applications of large language models in autonomous vehicles;
- Integrated planning and control frameworks;
- Cooperative motion planning and control;
- Energy management in autonomous vehicles;
- Reviews of motion planning and control;
- Reviews of control strategies applied to autonomous vehicles.
Dr. Tantan Zhang
Dr. Bai Li
Dr. Oscar Vento
Guest Editors
Manuscript Submission Information
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Keywords
- autonomous vehicles
- energy management
- end-to-end learning
- integrated planning and control
- large language models
- motion planning
- optimization
- simulation
- trajectory planning
- trajectory tracking and control
- validation and evaluation
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