Forecast of the Feasibility of Aviation-to-Automotive Methods Transfer by Empirical Quantification

Read full text
Authors: Yusuf Akkus, Björn Annighöfer
Cited by: 1
References: 15

Abstract

Abstract This study introduces an empirical approach to quantify the feasibility of transferring development methods across domains. The approach evaluates transfer proposals using an overall feasibility score and specific criteria such as cost, quality, and time. The Project Management Triangle was selected as the basis for this decision tool because its constraints can be quantified. The model produces a score on a scale from 0 to 10, based on two elements: the impact on automotive development and the relevance for automotive practices. Relevance was determined through a survey of 126 engineers from a commercial vehicle manufacturer, focusing on preferences regarding methods, processes, and tools. Survey results were used to weight the three constraints, improving forecast accuracy for the automotive domain. Model validation employed a previous study on common cause analysis for redundant chassis control systems, where aviation best practices were adapted for automotive. Engineers who applied gave their observed score. The forecasted feasibility score of 6.758 was compared with an observed score of 5.833, yielding an accuracy of 14%, which classifies the model as good. The proposed method offers three contributions: it provides a quantified feasibility assessment for cross-domain transfers, combines qualitative and quantitative indicators, and customizes weighting based on target group relevance. Limitations include reliance on data from a single manufacturer and validation based on one-method transfer. Overall, the approach demonstrates potential as a decision-support tool for reducing risks in cross-domain technology adoption.

Fields of Study & Subjects

Safety Systems Engineering in Autonomy Systems Engineering Methodologies and Applications Transportation Systems and Infrastructure

Publication details

Journal / source
Journal of Autonomous Vehicles and Systems
Publisher
ASME International
Volume
6
Issue
4
Publication date
13 May 2026
Language
EN