• Login
    View Item 
    •   DSpace Home
    • ASME
    • Journal of Autonomous Vehicles and Systems
    • View Item
    •   DSpace Home
    • ASME
    • Journal of Autonomous Vehicles and Systems
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

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

    Thumbnail
    View/Open
    javs-26-1006.pdf (1.379Mb)
    Date
    2026
    Author
    Akkus, Yusuf
    Annighöfer, Björn
    Metadata
    Show full item record
    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.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4315929
    Collections
    • Journal of Autonomous Vehicles and Systems

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV