Simulation is an integral part in the process of developing autonomous vehicles and advantageous for training, validation, and verification of driving functions. Even though simulations come with a series of benefits compared to real-world experiments, various challenges still prevent virtual testing from entirely replacing physical test-drives. Our work provides an overview of these challenges with regard to different aspects and types of simulation and subsumes current trends to overcome them. We cover aspects around perception-, behavior- and content-realism as well as general hurdles in the domain of simulation. Among others, we observe a trend of data-driven, generative approaches and high-fidelity data synthesis to increasingly replace model-based simulation.
@article{arxiv.2305.13960,
title = {From Model-Based to Data-Driven Simulation: Challenges and Trends in Autonomous Driving},
author = {Ferdinand Mütsch and Helen Gremmelmaier and Nicolas Becker and Daniel Bogdoll and Marc René Zofka and J. Marius Zöllner},
journal= {arXiv preprint arXiv:2305.13960},
year = {2023}
}
Comments
Ferdinand M\"utsch, Helen Gremmelmaier, and Nicolas Becker contributed equally. Accepted for publication at CVPR 2023 VCAD workshop