TESTING AUTONOMOUS CARGO VEHICLES AT AIRPORTS – AN ANALYSIS OF THE BASIC REQUIREMENTS FOCUSING ON STAFF-RELATED HUMAN FACTORS

Abstract

The air cargo industry is increasingly turning towards autonomous handling vehicles. Research so far has not fully explored how these vehicles affect human staff at airports. This paper presents a mixed-methods study, utilizing a three-stage approach including process analysis and expert interviews, followed by merging both thematic analyses in an adapted SHELL model. The SHELL model is found to be an effective tool for analysing the various types of interaction between the human factors and autonomous vehicles in their distinct environment.

The conclusion of the paper emphasizes the importance of considering human factors, including change management, process optimization, resilience, and others, to successfully integrate autonomous vehicles into airport operations. For instance, the application of the SHELL model highlights that autonomous vehicles require an adapted environment with advanced road infrastructure for effective communication and navigation. These changes may impact daily work routines, dispatch procedures, communication protocols, emergency response plans, and operational processes.