Generative AI and Neural Representations for Intelligent Sensing and Cooperative Perception in Autonomous Vehicles
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 8
Special Issue Editor
Interests: autonomous vehicles; computer vision; drones
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Generative AI and neural representations are transforming how autonomous and connected systems; on the ground, in the air, and at sea, perceive, understand, and interact with their surroundings. Modern mobility increasingly relies on intelligent sensing, multimodal data fusion, and semantic reasoning to ensure safe, adaptable, and efficient operation in both passenger and freight transportation.
Recent progress in Vision-Language Models (VLMs), Large Language Models (LLMs), and Neural Scene Representations, such as Neural Radiance Fields and Gaussian Splatting, has opened new possibilities for environmental modeling, cross-modal reasoning, and generative simulation. Combined with advanced sensing technologies, these approaches are redefining perception tasks, including object detection, tracking, semantic segmentation, and scene reconstruction.
This Special Issue invites original contributions exploring how foundation models, neural representations, and generative techniques can enhance sensor-driven perception, infrastructure intelligence, and autonomous mobility, from sensing and localization to decision-making and simulation. Both theoretical developments and experimental studies are encouraged, with applications across vehicles, drones, and smart infrastructures.
Topics of interest include, but are not limited to, the following:
- Object detection, tracking, and classification using sensor and AI-based fusion
- Vision-Language Models (VLMs) and Large Language Models (LLMs) for perception and reasoning
- Neural scene representations for driving, aerial, and infrastructure environments
- Dataset augmentation and synthetic scene generation using neural fields
- Semantic reasoning and understanding with neural representations
- Cross-modal alignment among vision, language, LiDAR, and radar data
- Generative world modeling and digital twin creation for mobility ecosystems
- Cooperative perception between vehicles, drones, and intelligent infrastructure (V2X)
- Anomaly detection and prediction using generative or world model-based approaches
- Simulation-based validation and training for perception and control systems
- Edge-AI, efficient deployment, and scalability of foundation models
- Safety, robustness, and interpretability in generative perception systems
By connecting sensors, AI, and semantics, this Special Issue aims to highlight the emerging convergence between generative intelligence and autonomous mobility, encouraging innovative research toward safer, smarter, and more connected transportation systems.
Dr. Abdulla Al-Kaff
Guest Editor
Manuscript Submission Information
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Keywords
- generative AI
- vision-language models (VLMs)
- large language models (LLMs)
- neural scene representations
- object detection
- dataset augmentation
- semantic perception
- digital twins
- anomaly detection
- cooperative perception
- smart infrastructure
- autonomous vehicles
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