Engineering Autonomous Driving Software

TL;DR

This paper presents an adaptable engineering process for developing autonomous driving AI, emphasizing agile methods, continuous integration, and a simulate-first testing approach for complex urban scenarios.

Contribution

It introduces a comprehensive software and systems engineering process tailored for autonomous vehicles, integrating agile practices and modular simulation testing.

Findings

Effective testing in urban scenarios through simulation.

Integration of agile and continuous development practices.

Enhanced reliability in autonomous vehicle software development.

Abstract

A larger number of people with heterogeneous knowledge and skills running a project together needs an adaptable, target, and skill-specific engineering process. This especially holds for a project to develop a highly innovative, autonomously driving vehicle to participate in the 2007 DARPA Urban Challenge. In this contribution, we present essential elements of a software and systems engineering process to develop a so-called artificial intelligence capable of driving autonomously in complex urban situations. The process itself includes agile concepts, like a test first approach, continuous integration of all software modules, and a reliable release and configuration management assisted by software tools in integrated development environments. However, one of the most important elements for an efficient and stringent development is the ability to efficiently test the behavior of the developed system in a flexible and modular system simulation for urban situations both interactively and unattendedly. We call this the simulate first approach.