Occupant Packaging Research Articles

Developing Customer Loss Function for Door Opening Angle in Passenger Cars: Balancing the Ergonomic Performance between “Entry/Exit (Ingress/Egress) Accommodation” and Door Reachability

<div>Occupant packaging is one of the key tasks involved in the early architectural phase of a vehicle. Accommodation, as a convention, is generally considered related to a car’s interior. Typical roominess metrics of the occupant like hip room, shoulder room, and elbow room are defined with the door in its closed condition. Several other roominess metrics like knee room, leg room, head room, and the like are also specified. While all the guidelines are defined with doors in their closed condition, it is also important to consider the dynamics that exist while the occupant is entering the vehicle. This article expands the traditional understanding of occupant accommodation beyond conventionally considering the vehicle interior’s ability to accommodate anthropometry. It broadens the scope to include dynamic conditions, such as when doors are opened, providing a more realistic and practical perspective. As a luxury car manufacturer, it is important to ensure the best overall customer experience at each touch point of the vehicle. When the customer enters the vehicle, there should be sufficient space provided by the door opening angle for a comfortable entry. The larger the opening angle, the better is the “entry accommodation” and vice versa. However, a wide-open door also necessitates the customer to bend more, after being seated, to reach its handle and close it. Thus, it becomes a compromise between what is possible as accommodation while the customer is entering the vehicle and how easy it is to close the door after being seated. The same logic holds good while the customer opens the door and exits the vehicle. This article aims to develop a customer loss function (CLF) between the two conflicting criteria by considering relevant anthropometric distribution of customers. This study focuses on driver compartment and the methodology developed is also pertinent to rear compartment with minor adaptations. Since driver’s seating position is heavily dependent on anthropometry, finer details of occupant seating position are also considered in this study. CLF developed in this article will help the designer and packaging engineers in making informed decisions on the door opening angle, by being conscious of the customer loss/gain for defined performance metrics.</div>

The Development of the Driving Simulator: Anthropometry and Occupant Packaging Evaluation in Ergonomic Study

The primary purpose of this study was to produce a driving simulator guided by ergonomics and anthropometry in the population of Malaysians. The data obtained from previous studies on the Malaysian population are minimal, so this study should be highlighted in the automotive research industry. Hence, this study also aimed to improve the existing study, where the driving simulator can investigate driving behavior systematically and in more detail. Furthermore, the simulator can produce the same scenario on the road without involving actual vehicles. Therefore, using a driving simulator can reduce the risk and cost of the study done on a real road. The used monitor will broadcast the setup road scenario on the display that will be observed and evaluated afterward. The research observed anthropometry data from 103 participants in 23 different measurements of 11 standing and 12 sitting positions. This analysis continues with the study of occupant packaging measurement in an actual vehicle's driving area, determining the driving simulator dimension. The driving simulator design is then obtained by analyzing three different vehicle models: BMW i3, Toyota Prius, and Proton Preve. This phase includes the standard and optimum driver seat adjustment according to the required ergonomics study, which is proportional to the Malaysian population measurement based on the selected previous study. The design proceeds with the material selection with aluminum extrusion as its design material. Finally, the design created is analyzed in a CATIA V5 simulation to examine the displacement magnitude and von Mises stress of the rig frame structure when some load is appointed. The final phase included a physical test to measure the driving simulator's abilities to avoid the stated obstacles in measuring its accuracy compared to an actual on-road experiment. This phase included 10 participants with two different scenarios. Participants had a compulsory questionnaire to conclude the analysis based on their experience. In conclusion, this study discriminated against on-road driving behavior with high safety factors and low cost without involving an actual vehicle or road. Hence, the simulation of the designed product proves that the subject weight is directly proportional to the displacement magnitude and its von Mises stress, and vice versa.

Evaluating lower body driving posture regarding gas pedal control and emergency braking: A pilot study

Lower body posture influences driving comfort and safety. The posture recommendations from the literature, however, are often based on preferred postures and can be inconsistent due to differences in the experimental setups. Furthermore, the ranges of preferred postures focusing on sitting comfort are often wide and, therefore, difficult to use for occupant packaging in the automotive industry. To cope with these issues, we developed a task-oriented approach to evaluate the lower body driving posture. We predefined 12 seating positions (4 knee angles × 3 seating heights) and measured the physical strain, discomfort perception, and task performance of gas pedal control and emergency braking. Results of the 11 participants showed that seating closer to the front with a 110° knee angle caused more foot dorsiflexion for gas pedal control and increased the right leg's shin muscle activity and discomfort; seating further back with a 145° knee angle decreased emergency braking performance. In conclusion, our new approach is feasible for objectively and effectively evaluating lower body driving posture. Relevance to industryThe approach of this study can provide a new perspective on the driving posture assessment. The findings can be utilized to optimize the occupant packaging process in the automotive industry.

Development of statistical geometric models for prediction of a driver's hip and eye locations

The Society of Automotive Engineers (SAE) J1517 and J941 models of a driver-selected seat position and a driver's eye location mainly rely on their statistical linear relationships with seat configuration and package variables. Although the SAE models are useful for vehicle interior design, their prediction performance was not provided. The present study was intended to develop accurate prediction models of a driver's hip location (HL) and eye location (EL) based on their statistical geometric relationships with anthropometric dimensions and driving postures. A driving simulation experiment was conducted with 40 Korean drivers (20 males and 20 females) in a seating buck reconfigurable to various package conditions. The anthropometric measurements, HLs, ELs, and joint angles of the participants were collected using an anthropometer, a motion capture system, and a digital human model simulation program. Two types (full model and simplified model) of statistical geometric models (SGMs) for HL and EL prediction were developed by multiple regression analysis of the anthropometric measurements and driving postures on the HLs and ELs. The average adjusted R2 and RMSE of the SGMs were .82 (± .06) and 25.7 (±3.3) mm, respectively. The SGMs showed accurate and stable prediction performance because the SGMs additionally incorporated the geometric relationships of HL and EL with anthropometric dimensions and joint angles. The SGMs would be useful to predict the HLs and ELs of drivers with various body sizes and joint angles in occupant packaging.

ELDERLY DRIVER INGRESS AND EGRESS FROM A VEHICLE: PERCEIVED DISCOMFORT AND TASK DURATION

The time it takes a driver to get in and out of a vehicle, and how comfortably they can perform this task, are important considerations for vehicle design. Older drivers are keeping their licenses longer and driving more miles, making it more important than ever to study how vehicle design parameters interact with the sensorimotor changes due to aging and disease. 48 older subjects (27 males, 21 females) between the ages of 67 and 89 years were tested. Twenty-four were healthy, 12 had osteoarthritis and 12 had diabetic polyneuropathy. Subjects completed both physical capacity tests and motion capture testing of ingress/egress in seven different vehicles represented by the Human Occupant Package Simulator. A control group of 48 younger drivers also completed ingress/egress testing. Motions, captured using Vicon cameras, were used to calculate the main outcome variables of Ingress Time and Egress Time. The third main outcome, Perceived Discomfort, was measured by asking the subjects to rate each ingress/egress motion. Inverse Egress Time and Discomfort were significantly correlated, with a correlation coefficient of -0.45. Longer times were associated with greater discomfort. Linear mixed-effect modeling showed that vehicle design factors that significantly influenced the discomfort or the duration of ingress/egress were the height of the vehicle seat with respect to the ground, as well as the location of the seat with respect to the sill and the roof rail. In conclusion, Perceived Discomfort and Ingress/Egress Time provide guidance on how vehicle design can improve the driving experience for elderly drivers.

Development of Statistical Models for Predicting a Driver’s Hip and Eye Locations

Regression equations for estimation of a driver’s hip location (HL) and eye location (EL) using the driver’s anthropometric and posture variables have been developed for US drivers. However, those equations are limited to US drivers and do not include seat adjustment variables (e.g., cushion angle) that may affect a driver’s HL and EL. The present study developed statistical models for prediction of a driver’s HL and EL using seat configurations including (1) fore-aft seat position, (2) seat height, (3) seat back recline angle, and (4) seat cushion angle. Driving postures of 23 Korean drivers (10 females and 13 males) were measured in a seating buck after adjusting seat configurations according to their preferences. The seat configurations, HLs, ELs, and joint angles of the participants were collected by a motion capture system. HL and EL prediction models based on the seat configurations and driving postures were developed by stepwise regression. The proposed models showed high accuracy (adj. R2 = .83 ± .13, RMSE = 19.1 ± 4.2 mm) in prediction of HL and EL. The performance difference between the seat configuration- and posture-based models was not statistically significant. The proposed seat configuration-based models can be used for accurate estimation of a driver’s HL and EL for occupant packaging layout design.

Implementation of Suitable Comfort Model for Posture and Motion Prediction in DHM Supported Vehicle Design

Driver-vehicle interaction analyses are done to ensure a successful vehicle design from an ergonomics perspective. Digital Human Modelling (DHM) tools are often used to support such verifications, particularly at early stages of the product development process. When verifying that a vehicle design accommodates the diversity of users and tasks, a DHM tool needs to be able to represent postures and motions that are likely under certain conditions. This functionality is essential so that the tool user will obtain objective and repeatable simulation results. The DHM tool IMMA (Intelligently Moving Manikins) predicts postures and motions by using computational methods. This offers the possibility to generate postures and motions that are unique for the present design conditions. IMMA was originally developed for simulating manual assembly work, whereas the work presented here is a step towards utilizing the IMMA tool for occupant packaging and related tasks. The objective is a tool for virtual verification of driver-vehicle interaction that supports and automates the simulation work to a high degree. The prediction functionality in IMMA is based on the use of optimization algorithms where one important component is the consideration of comfort level. This paper reports results from an basic investigation of driving postures and available comfort models suitable in a driving context, and shows initial results of seated posture and motion prediction functionality in the IMMA tool.

A Classification of Sitting Strategies based on Driving Posture Analysis

Objective: The present study is intended to objectively classify upper- & lower-body sitting strategies and identify the effects of gender and OPL type on the sitting strategies.BRBR Background: A sitting strategy which statistically represents comfortable driving posture can be used as a reference posture of a humanoid in virtual design and evaluation of a driver"s seat. Although previous research has classified sitting strategies for driving postures in various occupant package layout (OPL) types, the existing classification methods are not objective and the factors affecting sitting strategies have not been identified.BRBR Method: Forty drivers" preferred driving postures in three different OPL types (coupe, sedan, and SUV) were measured by a motion capture system. Next, the measured driving postures were classified by K-means cluster method. BRBR Results: Sitting strategies of upper-body were classified as erect (33%), slouched (41%), and reclined (26%) postures, and those of lower-body were classified as knee bent (42%), knee extended (32%), and upper-leg lifted (26%) postures. Significant differences at α = 0.05 in the upper-body sitting strategy by gender and lowerbody sitting strategy by OPL type were found.BRBR Application: Both the classified sitting strategies and the identified factors would be of use in ergonomic seat design and evaluation.

An envelope generation algorithm for packing and layout applications

In this paper, an algorithm and associated procedure for computing the envelope of non-convex manifold objects is proposed. The envelope generation algorithm is developed in the context of vehicle packaging and layout and is intended for use during the conceptual phase of the vehicle design process. The envelope generation algorithm presented in this paper is designed to work with complex manifold geometry and can be interpreted as the non-convex hull of an object (or a set of objects). The algorithm presented in this paper is primarily intended for probabilistic envelope generation based on spatial occupancy, however it can also be used to generate the envelope of a set of objects, envelope with a desired offset from the outer surface of the object, and motion envelope of an object. The proposed method is based on voxelization of the manifold geometry and thus it converts surface representation into volumetric representation to generate the envelope. The proposed envelope generation algorithm is demonstrated on sufficiently complex hypothetical geometries and a real-world application of the proposed algorithm to vehicle occupant packaging is presented. This proposed envelope generation algorithm can reduce the design time and automate certain aspects of the vehicle design process.

Evaluation of four steering wheels to determine driver hand placement in a static environment

While much research exists on occupant packaging both proprietary and in the literature, more detailed research regarding user preferences for subjective ratings of steering wheel designs is sparse in published literature. This study aimed to explore the driver interactions with production steering wheels in four vehicles by using anthropometric data, driver hand placement, and driver grip design preferences for Generation-Y and Baby Boomers. In this study, participants selected their preferred grip diameter, responded to a series of questions about the steering wheel grip as they sat in four vehicles, and rank ordered their preferred grip design. Thirty-two male participants (16 Baby Boomers between ages 47 and 65 and 16 Generation-Y between ages 18 and 29) participated in the study. Drivers demonstrated different gripping behavior between vehicles and between groups. Recommendations for future work in steering wheel grip design and naturalistic driver hand positioning are discussed.

Development of a consistent continuum of the dimensional parameters of a vehicle for optimization and simulation

Parametric vehicle modeling permits rapid iteration and optimization of vehicles in the conceptual design phase. A significant portion of vehicle design can be optimized parametrically without knowing specific details based on computer-aided design. Many overall characteristics of a vehicle such as the curb mass, the location of the center of gravity, the key dimensions, the occupant packaging, and the cargo volume can be assessed and improved at the parametric level. Targets for the vehicle such as the 0–60 mile/h acceleration time, the stopping distance, the fuel economy, the low-speed turn radius and aspects of the vehicle dynamics and handling can also be determined to a high level of confidence. In developing the vehicle’s dimensions for a parametric model it is recommended that a vehicle is built up using an ‘inside-out’ approach centered on effective knowledge-based occupant packaging. This work develops a continuum of the dimensional parameters which tie the vehicle’s internal and external dimensions together; it employs a combination of industry standard dimensions and component dimensions defined by the present authors, which make up the outside dimensions of the overall vehicle. In order to develop and optimize models for a desired vehicle type and size class, a knowledge base of typical values for the key dimensional parameters of a vehicle was compiled using a combination of data sources and field measurements. These values provide a useful starting point for the vehicle design and optimization process. They also increase optimization effectiveness, reducing the likelihood of local minima and maxima, and ensure that optimization begins within a valid design space.

운전석 체압분포 기반의 착좌전략 분류

Automotive Research and Development Division, Hyundai Motor Group, Uiwang, Gyeonggi-do, 437-815, KoreaDrivers’ sitting strategies are considered in car seat design. Existing research has identified representative sitting strategies by visual inspection of seating pressure measurements collected from a small sample size of drivers. The present study recruited 20 female and 20 male participants, measured seating pressure, and classified sitting strategies by cluster analysis. The participants’ sitting postures were classified based on seating pressure distribution into mid-back and scapular, mid-back and lumbar, and lumbar sitting strategies for the upper body and hip concentrated, hip and mid-thigh concentrated, and hip and mid-thigh distributed sitting strategies for the lower body. The effects of gender and occupant package layout (OPL) on sitting strategy were nout found significant. The identified sitting strategies would be of use for the design and evaluation of an OPL and a seat.

Ergonomic evaluation of interior design of Shoka vehicle and proposing recommendations for improvement

One of the applications of ergonomics disciplinary is designing driver workstation compatible to users' characteristics. The aim of this study was evaluation of interior design of Shoka vehicle with respect to the accommodation for Iranian population and proposing suggestions for customizing design of this vehicle. This study was a descriptive-analytical study conducted among thirty men from Iranian drivers population in 5, 50, 95 percentiles of the stature variable. Objective variables related to the occupant packaging and vehicle visual aspects including anthropometric variables, frontal, lateral, and side view and so on were investigated first. Then, subjective variables related to the driver mental workload and body comfort discomfort were studied using BMDMW and comfort questionnaires during 2-hour driving trial sessions. Occupant packaging variables and hand-arm angle showed the least accommodation percent (%53). Seating angles showed low accommodation as well (%73). Among three percentile groups there were no significant differences between the mean values of mental workload during two hours driving task. And, the mean value related to the comfort discomfort was 3.9 during driving sessions. Considering the findings in this study, it can be conclude that seating angles need correction and optimization. Taking mental workload results into account, it can be concluded that the interior design of the studied car had no influence on drivers' mental workload. From the aspect of comfort discomfort, Shoka vehicle showed neutral state among drivers. Optimizing seating angles, decreasing vibration, correcting stiffness of seating pan are suggested for customization of the ergonomics aspect of this vehicle.

User-centred interior design of a small electric vehicle using RAMSIS

Digital human models are essential for the development of vehicle interiors and driver workplaces. They can be used during the occupant packaging process to develop the seat, steering-wheel and pedals adjustment ranges to ensure optimal posture for occupants of different anthropometric measurements. However, digital human models can also be used to design the display and control concept during the early phases of the product development process. In this article the ergonomic interior design process of the electric vehicle MUTE is shown exemplarily. In addition to a discussion of different design principles of the driver's workplace, the simulation capabilities of RAMSIS and the tool RAMSIS cognitive are explained using the example of the design of a central touchscreen, which acts as the main input device for secondary and tertiary tasks.

Understanding and modelling heterogeneity of human preferences for engineering design

In today's competitive market, it is essential for companies to provide products which not only achieve high performance, but also appeal to the tastes of consumers. Therefore, a key element of design is an understanding of consumer preferences for product features. In this work, the random-effects ordered logit model is proposed as the modelling framework to capture the impact of both product and human attributes on consumers’ ratings of qualitative system and sub-system attributes. To support the modelling, a series of methodologies are developed to both understand and model the influence of consumer heterogeneity upon product preferences. To illustrate the methodologies, a human appraisal experiment for understanding preferences for automobile occupant package design is analysed. An issue with analysing human appraisal experiments is that the effect of respondent heterogeneity must be understood to separate the influence of design factors from that of human factors. Hierarchical Bayes estimation and cluster analysis are used to gain an understanding of respondent rating styles, which are subsequently modelled explicitly in the ordered logit model. Smoothing spline regression is used to determine the functional form of the ordered logit model. The proposed ordered logit model is validated using a vehicle design case study.

Integrated Bayesian Hierarchical Choice Modeling to Capture Heterogeneous Consumer Preferences in Engineering Design

Choice models play a critical role in enterprise-driven design by providing a link between engineering design attributes and customer preferences. However, existing approaches do not sufficiently capture heterogeneous consumer preferences nor address the needs of complex design artifacts, which typically consist of many subsystems and components. An integrated Bayesian hierarchical choice modeling (IBHCM) approach is developed in this work, which provides an integrated solution procedure and a highly flexible choice modeling approach for complex system design. The hierarchical choice modeling framework utilizes multiple model levels corresponding to the complex system hierarchy to create a link between qualitative attributes considered by consumers when selecting a product and quantitative attributes used for engineering design. To capture heterogeneous and stochastic consumer preferences, the mixed logit choice model is used to predict consumer system-level choices, and the random-effects ordered logit model is used to model consumer evaluations of system and subsystem level design features. In the proposed approach, both systematic and random consumer heterogeneity are explicitly considered, the ability to combine multiple sources of data for model estimation and updating is provided using the Bayesian estimation methodology, and an integrated estimation procedure is introduced to mitigate error propagated throughout the model hierarchy. The new modeling approach is validated using several metrics and validation techniques for behavior models. The benefits of the IBHCM method are demonstrated in the design of an automobile occupant package.

운전자 정적 거동 특성을 이용한 차량 패키지 개선용 등가 인지지도 개발

This study was aimed at developing I) iso-perception maps for various groups of drivers in terms of age, gender, and anthropometry and 2) the experiment framework required for obtaining subjective and objective measures. A total of 9 maps, which describe drivers' perceptions regarding their static behaviors inside a typical mid-size sedan, can be used to improve the utilization of the limited driver workspace, and to select better design altematives for occupant packaging. An adjustable seating buck, a<SUP>***</SUP>-camera motion capture system (Vicon), and a<SUP>**</SUP>-chmmel EMG system were used for the experiment. Each iso-perception map was developed while H-PT, steering wheel center, or TGS knob center was moved to each of pre-defined positions relative to driver-selected positions. Adjustable ranges or positions of the seat, steering wheel, and TGS lever described in iso-perception maps can be used to detennine better package layout altematives.

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

The use of customer preference models to evaluate the economic impact of design changes and new product introductions has become prevalent in the literature. However, existing approaches do not sufficiently address the needs of complex design artefacts, which typically consist of many subsystems and components designed and manufactured with significant autonomy. Characteristics of complex systems, such as heterogeneity of consumer preferences throughout the system hierarchy, multiple sources of information and qualitative consumer-desired attributes, have not been adequately addressed. In this work, we propose a hierarchical choice modelling approach for complex systems to model customer preferences for attributes throughout the system hierarchy, and to subsequently predict consumer choice behaviours. A system of hierarchical models is used to link the design attributes used for engineering design to the attributes used by consumers to choose among competing products. The model framework utilises Discrete Choice Analysis at the top level to model customer choices and Ordered Logit regression at the lower levels to model ordinal survey responses as a function of product attributes. An approach for combining choice data from multiple sources based on the Nested Logit methodology is developed. The framework is demonstrated on the vehicle occupant package case study.

Digital human modelling for user-centred vehicle design and anthropometric analysis

Digital human modelling (DHM) is discussed as a design tool in the context of user-centred design, with a focus on DHM usage for anthropometric analysis in occupant packaging tasks in the vehicle interior design process. References are made to concepts of inclusive design, user-centred design, design cognition and design methodology. Examples are presented to illustrate how DHM can be of great use to the vehicle designer, but also to show some of the difficulties involved. This includes the complexity in considering anthropometric variation of the targeted product users in multivariate design problems, such as the design of vehicle interiors and suggestions on how to deal with this difficulty in an industrial design setting. Overall, the paper takes a designer's view of DHM tools and illustrates how the tools can be of value in the design process, but also considers what implications this has on the functionality and usability of the tools.

Development of a hierarchical estimation method for anthropometric variables

Most regression models of anthropometric variables use stature and/or weight as regressors; however, these ‘flat’ regression models can produce large errors in estimation for anthropometric variables having low correlations with the regressors. A novel method was proposed which estimates anthropometric variables in a hierarchical manner based on the geometric and statistical relationships between the variables. This hierarchical estimation method first constructs estimation structures by analyzing the dimensional characteristics and geometric relationships of the anthropometric variables and then develops regression models based on the estimation structures. The hierarchical estimation method was applied to 60 anthropometric variables (selected for the design of an occupant package layout in a passenger car) by using the 1988 US Army anthropometric survey data. The hierarchical regression models showed a 55% increase in adjusted R 2 and a 31% decrease in SE on average when compared with corresponding flat regression models. Relevance to industry Regression models of anthropometric variables are of use in ergonomic design of products and workplaces when necessary body measurements are unavailable. The proposed hierarchical estimation method can be applied effectively to establish regression models of anthropometric variables, which have better statistical performance and geometrical meaning.