# Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving

## TL;DR

This paper analyzes the transfer of an open source autonomous driving stack to a research vehicle, providing insights and lessons learned to facilitate faster setup for future research platforms.

## Contribution

It presents a detailed case study of adapting an open source driving stack to a research vehicle, including hardware/software choices and integration lessons.

## Key findings

- Mapping of Apollo stack to research vehicle system layout
- Real-time communication with actuators implemented
- Lessons learned to accelerate future system setups

## Abstract

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.