EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application
Abstract
While current research and development of autonomous driving primarily focuses on developing new features and algorithms, the transfer from isolated software components into an entire software stack has been covered sparsely. Besides that, due to the complexity of autonomous software stacks and public road traffic, the optimal validation of entire stacks is an open research problem. Our paper targets these two aspects. We present our autonomous research vehicle EDGAR and its digital twin, a detailed virtual duplication of the vehicle. While the vehicle's setup is closely related to the state of the art, its virtual duplication is a valuable contribution as it is crucial for a consistent validation process from simulation to real-world tests. In addition, different development teams can work with the same model, making integration and testing of the software stacks much easier, significantly accelerating the development process. The real and virtual vehicles are embedded in a comprehensive development environment, which is also introduced. All parameters of the digital twin are provided open-source at https://github.com/TUMFTM/edgar_digital_twin.
Cite
@article{arxiv.2309.15492,
title = {EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application},
author = {Phillip Karle and Tobias Betz and Marcin Bosk and Felix Fent and Nils Gehrke and Maximilian Geisslinger and Luis Gressenbuch and Philipp Hafemann and Sebastian Huber and Maximilian Hübner and Sebastian Huch and Gemb Kaljavesi and Tobias Kerbl and Dominik Kulmer and Tobias Mascetta and Sebastian Maierhofer and Florian Pfab and Filip Rezabek and Esteban Rivera and Simon Sagmeister and Leander Seidlitz and Florian Sauerbeck and Ilir Tahiraj and Rainer Trauth and Nico Uhlemann and Gerald Würsching and Baha Zarrouki and Matthias Althoff and Johannes Betz and Klaus Bengler and Georg Carle and Frank Diermeyer and Jörg Ott and Markus Lienkamp},
journal= {arXiv preprint arXiv:2309.15492},
year = {2024}
}