Managing Human Factors and Requirements in Agile Development of Automated Vehicles: An Exploration

Licentiate thesis, 2022

Context: Automated Vehicle (AV) technology has evolved significantly in
complexity and impact; it is expected to ultimately change urban transporta-
tion. However, research shows that vehicle automation can only live up to this
expectation if it is defined with human capabilities and limitations in mind.
Therefore, it is necessary to bring human factors knowledge to AV developers.

Objective: This thesis aims to empirically study how we can effectively
bring the required human factors knowledge into large-scale agile AV develop-
ment. The research goals are 1) to explore requirements engineering and human
factors in agile AV development, 2) to investigate the problems of requirements
engineering, human factors, and agile way of working in AV development, and
3) to demonstrate initial solutions to existing problems in agile AV development.

Method: We conducted this research in close collaboration with industry,
using different empirical methodologies to collect data—including interviews,
workshops, and document analysis. To gain in-depth insights, we did a qualita-
tive exploratory study to investigate the problem and used a design science
approach to develop initial solution in several iterations.

Findings and Conclusions: We found that applying human factors
knowledge effectively is one of the key problem areas that need to be solved in
agile development of artificial intelligence (AI)-intense systems. This motivated
us to do an in-depth interview study on how to manage human factors knowl-
edge during AV development. From our data, we derived a working definition
of human factors for AV development, discovered the relevant properties of
agile and human factors, and defined implications for agile ways of working,
managing human factors knowledge, and managing requirements. The design
science approach allowed us to identify challenges related to agile requirements
engineering in three case companies in iterations. Based on these three case
studies, we developed a solution strategy to resolve the RE challenges in agile
AV development. Moreover, we derived building blocks and described guide-
lines for the creation of a requirements strategy, which should describe how
requirements are structured, how work is organized, and how RE is integrated
into the agile work and feature flow.

Future Outlook: In future work, I plan to define a concrete requirement
strategy for human factors knowledge in large-scale agile AV development.
It could help establishing clear communication channels and practices for
incorporating explicit human factors knowledge into AI-based large-scale agile
AV development.