[2603.17714] From Virtual Environments to Real-World Trials: Emerging Trends in Autonomous Driving

Computer Science > Artificial Intelligence arXiv:2603.17714 (cs) [Submitted on 18 Mar 2026 (v1), last revised 3 Apr 2026 (this version, v2)] Title:From Virtual Environments to Real-World Trials: Emerging Trends in Autonomous Driving Authors:A. Humnabadkar, A. Sikdar, B. Cave, H. Zhang, N. Bessis, A. Behera View a PDF of the paper titled From Virtual Environments to Real-World Trials: Emerging Trends in Autonomous Driving, by A. Humnabadkar and 4 other authors View PDF HTML (experimental) Abstract:Autonomous driving technologies have achieved significant advances in recent years, yet their real-world deployment remains constrained by data scarcity, safety requirements, and the need for generalization across diverse environments. In response, synthetic data and virtual environments have emerged as powerful enablers, offering scalable, controllable, and richly annotated scenarios for training and evaluation. This survey presents a comprehensive review of recent developments at the intersection of autonomous driving, simulation technologies, and synthetic datasets. We organize the landscape across three core dimensions: (i) the use of synthetic data for perception and planning, (ii) digital twin-based simulation for system validation, and (iii) domain adaptation strategies bridging synthetic and real-world data. We also highlight the role of vision-language models and simulation realism in enhancing scene understanding and generalization. A detailed taxonomy of datasets, tools...