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Automotive seats are commonly described by one-dimensional measurements, including those documented in SAE J2732. However, 1-D measurements provide minimal information on seat shape. The goal of this work was to develop a statistical framework to analyze and model the surface shapes of seats by using techniques similar to those that have been used for modeling human body shapes. The 3-D contour of twelve driver seats of a pickup truck and sedans were scanned and aligned, and 408 landmarks were identified using a semi-automatic process. A template mesh of 18,306 vertices was morphed to match the scan at the landmark positions, and the remaining nodes were automatically adjusted to match the scanned surface. A principal component (PC) analysis was performed on the resulting homologous meshes. Each seat was uniquely represented by a set of PC scores; 10 PC scores explained 95% of the total variance. This new shape description has many applications.

Seat fit is characterized by the spatial relationship between the seat and the vehicle occupant’s body. Seat surface pressure distribution is one of the best available quantitative measures of this relationship. However, the relationships between sitter attributes, pressure, and seat fit have not been well established. The objective of this study is to model seat pressure distribution as a function of the dimensions of the seat and the occupant’s body. A laboratory study was conducted using 12 production driver seats from passenger vehicles and light trucks. Thirty-eight men and women sat in each seat in a driving mockup. Seat surface pressure distribution was measured on the seatback and cushion. Relevant anthropometric dimensions were recorded for each participant and standardized dimensions based on SAE J2732 (2008) were acquired for each test seat.

Where is my head? Knowing head orientation in space is necessary to estimate the extent of the visual field in tasks requiring visual feedback such as driving or manual materials handling. Visually guided tasks are generally dependent on head and eye movements for visual acquisition of the target, and head movements are of significant importance when target eccentricity from the neutral reference point is large. The aim of the present work was to investigate head orientation in space in hand pointing tasks and to model the head response. Standing subjects were required to direct their gaze at one of three targets, equally distributed (vertically) in the sagittal plane. The task was performed while standing a) with the arms next to the body, b) holding a load in a static condition, c) aiming at targets with a heavy or light load held in the hands. Movements of the head and the body segments were recorded by the motion capture systems.