Journal of Air Transport Studies

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

Nadine Muecklich — 2025-11-21

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.

Examining the Effects of Market Concentration on Departure and Arrival On-Time Performance at Large Airports

K.P.D Frank Perera — 2025-11-21

This study explores the relationship between market concentration and on-time performance at major airports. It investigates whether higher market concentration levels are associated with improved or worsened flight punctuality. The research is based on extensive data from various airlines operating at these airports and provides valuable insights for airport operators, airlines, and policymakers. The findings indicate that variation in market concentration significantly impacts on-time performance. On-time performance decreases to approximately 0.6 to 0.7 in markets with heightened concentration and reduced competition. However, moderately concentrated markets demonstrate higher competition and relatively high on-time performance. These results provide policymakers with opportunities to enhance overall system performance through strategic interventions.

A Demonstrator for Interconnecting Independent Material Flow Simulation Models in the Air Cargo Supply Chain Using the IATA ONE Record Standard

Benjamin Bierwirth — 2025-11-21

In this paper we demonstrate the concept of a digital twin for the air cargo transport chain which is based on data provided via the new IATA ONE Record standard (1R). Using ONE Record data which is based on the linked data concept enables overarching optimization without the necessity to build interfaces to many legacy systems or share sensitive data between supply chain partners. Real shipment data was transformed into the 1R format and stored in GraphDB from where it was retrieved with SparQL to feed a simulation model built with Siemens Plant Simulation. The concept shows how certain activities can be used the predict the near-term workload of the downstream supply chain partners.