- Submissions due: 1 November 2023
- Publication: May/June 2024
In recent decades, the field of autonomous driving technology has witnessed remarkable growth. With the support of artificial intelligence, self-driving cars are transitioning from concept to reality, offering immense potential for reducing traffic accidents and transportation costs. However, despite the vast amounts of data generated by autonomous vehicles, it remains underutilized, particularly in the areas of visualization and visual analytics.
Numerous studies have underscored the importance of visualization in diagnosing, evaluating, and interpreting autonomous driving models. The high-dimensional, multimodal, and spatiotemporal nature of autonomous driving data presents significant challenges in leveraging visualization to reveal underlying correlations and patterns. By addressing these challenges, we can provide invaluable insights to benefit developers in the autonomous driving field.
The aim of this special issue is to advance the knowledge and understanding of autonomous driving through visual analytics, paving the way for novel insights and developments in this rapidly evolving domain. We invite contributions that explore innovative methodologies and effective applications of visualization and visual analytics methods in autonomous driving research.
Topics of interest include, but not limited to:
- Visual Exploration of Autonomous Driving Scenarios
- Spatiotemporal Visual Analytics for Traffic Data
- Interactive Annotation Tools for Autonomous Driving Data
- Explainable AI (XAI) in Autonomous Driving Algorithms
- Visualization and Visual Analytics of Autonomous Driving Data
- Visual Assessment of Autonomous Driving Performance
- Visual Pattern Mining in Autonomous Driving Data
- Visual Diagnosis of Autonomous Driving Models
- Visual Storytelling in Autonomous Driving Contexts
- Training Data Synthesis and Machine Learning for Autonomous Driving Applications
- Enhancing Navigation, Kinematics, Sensing, and Planning through Visualization Techniques
- User Interface and Interaction Design for Autonomous Driving Systems
- Interactive AI Toolboxes for Autonomous Driving Development
For author information and guidelines on submission criteria, visit the Author’s Information page. Please submit papers through the ScholarOne system and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by email to the guest editors directly.
Contact the guest editors at cga3-2024@computer.
- Siming Chen, Fudan University
- Liang Gou, Bosch Research
- Michael Kamp, Institute for AI in Medicine, and Ruhr-University Bochum
- Dong Sun, Nio.co