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: 30 June 2026 | Viewed by 3

Special Issue Editors


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Guest Editor
AutoMan Lab, Nanyang Technological University, Singapore, Singapore
Interests: autonomous driving; collective intelligence; continual learning

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Guest Editor
Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, China
Interests: human-robot interaction; computational modeling; interactive motion planning for autonomous driving; traffic safety

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Guest Editor
Department of Cognitive Robotics, Delft University of Technology (TU Delft), Delft, The Netherlands
Interests: autonomous driving; machine learning; AI-driven; human factor

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Guest Editor
National Engineering Research Center for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: autonomous driving; machine learning; AI-driven; motion planning; decision-making; energy management of hybrid electric vehicles
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: autonomous systems; robotics; multi-modal embodied AI; foundation models; human-in-the-loop AI; human-machine systems; codesign optimization
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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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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-blind 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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Published Papers

This special issue is now open for submission.
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