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A Matrix-Based Approach to Investigate the Geometrical Dependencies between Non-Driving-Related Tasks and Future Vehicle Concepts

Part of: Mobility

Published online by Cambridge University Press:  26 July 2019

Niko Seebach ,
Marcel Rück ,
Frank Arlt  and
Beate Bender
Niko Seebach*
Affiliation:
BMW AG; Ruhr-University Bochum
Marcel Rück
Affiliation:
BMW AG;
Frank Arlt
Affiliation:
BMW AG;
Beate Bender
Affiliation:
Ruhr-University Bochum
*
Contact: Seebach, Niko, BMW AG, Total Vehicle – Geometrical Concept Design, Integration, Germany, [email protected]

Abstract

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Caused by the technology of automated driving the user is temporarily released from driving and can perform non-driving-related tasks (NDRTs), such as sleeping or working. The aim of this paper is to describe the geometrical interdependencies between NDRTs and different vehicle types, to be able to integrate them in the geometric package of the early phase of the vehicle conception. To address the objective a literature based study of existing approaches for vehicle conception and NDRT-studies was carried out. Additionally interviews with n=15 experts from the automotive conception department and a databased analysis of n=259 vehicles was conducted. Based on these investigations 91 geometrical characteristics for NDRTs and vehicle types werde determined and combined through a matrix-based approach. By analysing the approach highly connected characteristics such as the torso angle were identified and equations were set up to describe the relations. The approach can be used for different NDRTs such as relaxing and working and different vehicle types such as sporty cars or SUVs in order to integrate them into the package.

Keywords

Conceptual designEarly design phasesComplexityNon-driving-related tasksVehicle package
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2815 - 2822
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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