Embodied Intelligence and Actuator Co-Design for Autonomous Vehicles
A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuators for Surface Vehicles".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 812
Editors
Interests: autonomous driving; collective intelligence; continual learning
Interests: human-robot interaction; computational modeling; interactive motion planning for autonomous driving; traffic safety
Interests: autonomous driving; machine learning; AI-driven; human factor
Interests: autonomous driving; machine learning; AI-driven; motion planning; decision-making; energy management of hybrid electric vehicles
Interests: autonomous systems; robotics; multi-modal embodied AI; foundation models; human-in-the-loop AI; human-machine systems; codesign optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Autonomous driving is shifting from modular pipelines to embodied intelligence powered by large models (LLMs, VLMs, and VLAs) that reason over perception, prediction, and control in a closed loop. This Special Issue seeks work that connects foundation models and continual learning with vehicle behavior and actuation constraints, emphasizing software-centric co-design rather than hardware specifics. We welcome studies on policy learning and decision-making with risk-aware reasoning, safe RL/IL, lifelong/continual learning under distribution shift, multi-agent interaction, and sim-to-real transfer. Contributions may include large-model planning and control, tool-use/action grounding, policy distillation and compression for on-vehicle deployment, verification and interpretability of model decisions, dataset and benchmark creation for actuation-aware evaluation, and digital-twin or HIL validation frameworks that close the gap between model reasoning and vehicle dynamics. Both theoretical and empirical works are encouraged, provided they clarify how model capacities, memory, and adaptation shape closed-loop performance, safety, and efficiency.
Dr. Zirui Li
Dr. Xiaocong Zhao
Dr. Xiaolin He
Dr. Guodong Du
Dr. Chen Lyu
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- embodied intelligence and actuator selection/placement
- integrated perception–control–actuation loops
- predictive and robust control
- learning-based approaches for actuation
- active chassis and motion control
- human-machine interaction
- co-optimization of energy and thermal management
- digital twins for actuator design and validation
- actuation systems for autonomous vehicles
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