Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving
This work addresses the gap in sharing engineering knowledge for autonomous driving research vehicles, enabling faster deployment by the research community, though it is incremental as it builds on existing open-source software.
The paper tackles the problem of transferring an open-source autonomous driving software stack (Apollo) to a research vehicle (fortuna), providing a detailed analysis of hardware-software integration and lessons learned to reduce setup efforts for other groups.
Although many research vehicle platforms for autonomous driving have been built in the past, hardware design, source code and lessons learned have not been made available for the next generation of demonstrators. This raises the efforts for the research community to contribute results based on real-world evaluations as engineering knowledge of building and maintaining a research vehicle is lost. In this paper, we deliver an analysis of our approach to transferring an open source driving stack to a research vehicle. We put the hardware and software setup in context to other demonstrators and explain the criteria that led to our chosen hardware and software design. Specifically, we discuss the mapping of the Apollo driving stack to the system layout of our research vehicle, fortuna, including communication with the actuators by a controller running on a real-time hardware platform and the integration of the sensor setup. With our collection of the lessons learned, we encourage a faster setup of such systems by other research groups in the future.