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Virtual drivers in math models can design and evaluate the seating package in all classes of vehicles. With the driver's seated geometry constrained by vision and reach to the steering wheel and pedal, seat design is optimized to support all drivers in three back postures to operate the vehicle. The position of each virtual driver model in the seat is calculated from a biomechanical model of seated load distribution with each model represented by functionally correct positions of pelvis and spine as well as the deflected shape of the seated body in a vehicle seat. This geometry is optimized to design or evaluate seats by changing boundary conditions of select variables and functions in the math tool. The math comfort score is calculated from the physical interface between the virtual drivers and the seating package. The weighted sum of scores for all virtual drivers is the population comfort score for the vehicle seating package.

A digital human body model is used to mathematically calculate occupant position in the vehicle package. The unoccupied seat shape that will support the digital human body model is optimized using a biomechanical model of the human body, a load-deflection model of the seat along with manufacturability and safety criteria. By unloading the seat at anatomically comparable landmarks for each digital human body model, as defined by gender and body size, the collection of points on the unoccupied seat surface define a patch. With 3 patches on the cushion and 4 patches on the back, two surfaces representing the centerline of the seat and seat insert can be defined for the population of occupants. This process can be done with constrained or unconstrained vehicle package geometry. The result is a “one seat fits all” design of the unoccupied deliverable seat given the requirements of the ergonomic task of driving the vehicle.

In this paper we present a method for converting the CAESAR full body scanned data into human body models for use in the ERL design software. The ERL software is a comprehensive interior automobile design tool, used in design or evaluation. The 3D CAD occupants in ERL were generated from anatomical cross sections at comparable landmarks and spinal shapes. Skeletal landmarks in the CAESAR data are used to establish segmental coordinates from which cross-sections are defined. The anatomical cross sections are used to re-generate the external shape of the body. Additional skeletal landmarks are calculated using regression equations. Segmental mass distributions are calculated based on segmental volume.

An advanced biofidelic shape of the human body is needed in computer-aided design (CAD) models for ergonomic design. To be used in seat and automotive design, this advance in biofidelity must be a 3D CAD tool that includes the deflected shape of the human body and must include skeletal landmarks, especially those related to load paths. The CAD tools must represent the range of the population and must also represent the full range of seated postures. To develop our CAD models, a 3D anthropometric study was undertaken that used skeletal landmarks to define relative positions of transverse cross-sections that describe both the “visible” and “invisible” shape of the seated body. Data were collected on large males, average males and small females. Subjects were measured in several postures while sitting on flat foam pads. Transverse sections were measured at the center of gravity of each thigh, under the ischial tuberosities and at the S2, L4, T8 and T4 spinal levels.

A new CAD-based model of the occupant/driver for interior and seat design has been developed. Unlike traditional automotive iterative design methods that begin with a 2D human manikin in an environment based on the location of H-point, the 3D ERL manikins determine the initial design positions of multiple occupants based on the simulated interactions of seat, driver package, skeletal linkage system and deflected human tissue. The 3D ERL human body representations come from measurements of posture-critical skeletal landmarks on 102 test subjects combined with measurements of “deflected human tissue” data from 60 test subjects. The result is a set of three dimensional, posture-biofidelic manikins that a computer algorithm optimizes the driver's workplace environment to fit the population range of sizes and postural preferences.