Software & Systems Engineering Process and Tools for the Development of Autonomous Driving Intelligence

TL;DR

This paper presents a comprehensive software and system engineering process tailored for developing autonomous driving AI, emphasizing agile practices, modular testing, and simulation for complex urban environments.

Contribution

It introduces a specialized engineering process integrating agile methods, testing, and simulation tools for autonomous vehicle development in urban scenarios.

Findings

Effective testing in modular urban simulators improves system reliability.

Agile practices like test-first and continuous integration enhance development efficiency.

Integrated tools support reliable release and configuration management.

Abstract

When a large number of people with heterogeneous knowledge and skills run a project together, it is important to use a sensible engineering process. This especially holds for a project building an intelligent autonomously driving car to participate in the 2007 DARPA Urban Challenge. In this article, we present essential elements of a software and system engineering process for the development of artificial intelligence capable of driving autonomously in complex urban situations. The process includes agile concepts, like test first approach, continuous integration of every software module and a reliable release and configuration management assisted by software tools in integrated development environments. However, the most important ingredients for an efficient and stringent development are the ability to efficiently test the behavior of the developed system in a flexible and modular simulator for urban situations.