A Parametric Approach to Vehicle Seating Buck Design

Wang, Nanxin; Wan, Jian; Gomez-Levi, Gianna

doi:10.1115/detc2004-57212

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…It is also important to allow users to experience the interior space of an autonomous vehicle that will change in the future to consider whether the proposed spatial design is appropriate and analyze the spatial design elements. Some studies used an existing vehicle model (seating buck) to assess various approaches to spatial design such as usability and ergonomics [25]. It is important to investigate the user experience in an autonomous vehicle model (seating buck) that incorporates a flexible spatial design in which the participants can freely use various components in the space.…”

Section: Prior Research On In-vehicle Activities and The Spatial Desi...mentioning

confidence: 99%

Spatial Components Guidelines in a Face-to-Face Seating Arrangement for Flexible Layout of Autonomous Vehicles

Kwon

2021

Electronics

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Fully autonomous vehicles are not yet available for consumers to experience; however, as experts predict they will be ready for the consumer market in the not-too-distant future, it is important to consider the spatial design of such vehicles. As the interior of a vehicle is a confined space, it is important to design a flexible layout in different aspects of the overall space. Therefore, this study aimed to analyze the relationships among various elements related to the use of space in a face-to-face seating arrangement. Using mock-up, observational surveys, questionnaires, and the think-aloud research method within an ethnographic observation framework, we conducted experiments on three study participants who were aware of the changing concept of autonomous vehicles. One of the key findings of our analysis is that various activities and actions can occur in a face-to-face seating arrangement. It is important to recognize that face-to-face seating arrangements are not just to facilitate conversation but can be seen as an environment in which each passenger can conduct other in-vehicle activities individually. Based on these findings, we recommend that needs for activities be considered when designing spatial components in a face-to-face seating arrangement.

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Section: Prior Research On In-vehicle Activities and The Spatial Desi...mentioning

confidence: 99%

Spatial Components Guidelines in a Face-to-Face Seating Arrangement for Flexible Layout of Autonomous Vehicles

Kwon

2021

Electronics

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“…Both production vehicles and seating bucks are used for package design consumer appraisals. In recent years, a computer-controlled seating buck, the Programmable Vehicle Model (PVM) (Wang et al, 2004, Wang et al, 2006 has been used for appraisals as it provides a quick and cost effective alternative to traditional seating bucks. PVMs can cover a wide range of vehicles, and can significantly cut the cost of building multiple seating bucks for design evaluation.…”

Section: Background To Vehicle Package Designmentioning

confidence: 99%

A hierarchical choice modelling approach for incorporating customer preferences in vehicle package design

Kumar

Hoyle

Chen

et al. 2009

IJPD

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Demand models play a critical role in enterprise-driven design by expressing demand and revenues as a function of price, and product attributes. Revenues and cost, expressed as a function of product attributes, provide the basis for predicting profits; the primary objective of corporate decision-making. However, existing demand modelling approaches in the design literature do not sufficiently address the unique issues that arise when complex systems are being considered. Current approaches typically consider customer preferences for only quantitative product characteristics and do not offer a methodology to incorporate customer preference-data from multiple component/subsystem-specific surveys to make product-level design trade-offs. In this paper, we propose a hierarchical choice modelling approach that addresses the special needs of complex engineering systems. The approach incorporates the use of qualitative attributes and provides a framework for pooling data from multiple sources. Heterogeneity in the market and in customer-preferences is explicitly considered in the choice model to accurately reflect choice behaviour. Ordered logistic regression is introduced to model survey-ratings and is shown to be free of the deficiencies associated with competing techniques, and a Nested Logit-based approach is proposed to estimate a system-level demand model by pooling data from multiple component/subsystemspecific surveys. The design of the automotive vehicle occupant package is used to demonstrate the proposed approach and the impact of both packaging design decisions and customer demographics upon vehicle choice are investigated. The focus of this paper is on demonstrating the demand (choice) modelling aspects of the approach rather than on the vehicle package design.

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“…Both production vehicles and seating bucks have been used for package design consumer appraisals. In recent years, a computer-controlled seating buck, the Programmable Vehicle Model (PVM) [33,34] has been used for appraisals as it provides a quick and cost effective alternative to traditional seating bucks. PVMs can cover a wide range of vehicles, and can significantly cut the cost of building multiple seating bucks for design evaluation.…”

Section: Background To Vehicle Package Designmentioning

confidence: 99%

Incorporating Customer Preferences and Market Trends in Vehicle Package Design

Kumar

Hoyle

Chen

et al. 2007

Volume 6: 33rd Design Automation Conference, Parts a and B

Self Cite

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Demand models play a critical role in enterprise-driven design by expressing revenues and costs as functions of product attributes. However, existing demand modeling approaches in the design literature do not sufficiently address the unique issues that arise when complex systems are being considered. Current approaches typically consider customer preferences for only quantitative product characteristics and do not offer a methodology to incorporate customer preference-data from multiple component/subsystem-specific surveys to make product-level design trade-offs. In this paper, we propose a hierarchical choice modeling approach that addresses the special needs of complex engineering systems. The approach incorporates the use of qualitative attributes and provides a framework for pooling data from multiple sources. Heterogeneity in the market and in customer-preferences is explicitly considered in the choice model to accurately reflect choice behavior. Ordered logistic regression is introduced to model survey-ratings and is shown to be free of the deficiencies associated with competing techniques, and a Nested Logit-based approach is proposed to estimate a system-level demand model by pooling data from multiple component/subsystem-specific surveys. The design of the automotive vehicle occupant package is used to demonstrate the proposed approach and the impact of both packaging design decisions and customer demographics upon vehicle choice are investigated. The focus of this paper is on demonstrating the demand (choice) modeling aspects of the approach rather than on the vehicle package design.

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A Parametric Approach to Vehicle Seating Buck Design

Cited by 5 publications

References 6 publications

Spatial Components Guidelines in a Face-to-Face Seating Arrangement for Flexible Layout of Autonomous Vehicles

Spatial Components Guidelines in a Face-to-Face Seating Arrangement for Flexible Layout of Autonomous Vehicles

A hierarchical choice modelling approach for incorporating customer preferences in vehicle package design

Incorporating Customer Preferences and Market Trends in Vehicle Package Design

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