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- W2044170856 abstract "Many applications exist where humans are required to perform a task in a seated position, such as operating a vehicle. Seated posture inside a vehicle influences driver performance and control of the vehicle. For people of extreme stature, tall or short, and for people of extreme width, obese or pregnant populations, it can be difficult to safely operate a vehicle if there is not enough room in the cab or if some controls cannot be reached. This study proposes a hybrid method for predicting the optimum driver seat adjustment range to accommodate diverse drivers in any vehicle based on a direct optimization-based posture prediction method. The proposed hybrid method combines three approaches: a boundary manikin approach, a population sampling approach, and a special population approach. The boundary manikin approach places two boundary manikins (5% female and 95% male) inside a virtual vehicle cab to perform tests. The population sampling approach spans a multitude of test subjects ranging in stature from 158 to 185 cm, determining the range from a plot of predicted hip point distances from the point of contact of the right heel and the floor. The special population approach studies the effect that size and shape changes, such as pregnancy, have on seated posture inside a vehicle. Also given is an indication of discomfort through the output values of the multi-objective function in the optimization formulation. A combination of the three approaches is used to determine an optimal adjustment range for the driver seat, thus allowing most people to safely operate the vehicle. Results of the simulations are validated using experimental determinations of the driver seat adjustment range from the literature. The main benefit of using this method is that the human aspect of design can be included early in the design process, thereby reducing or eliminating prototypes. Another benefit of the simulation is that it can be adapted to other seating tasks such as: occupant seat check inside a vehicle; workstation design; and issues related to other special populations such as obese individuals, dwarfs, and children." @default.
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- W2044170856 date "2012-01-01" @default.
- W2044170856 modified "2023-09-23" @default.
- W2044170856 title "Hybrid method for driver accommodation using optimization-based digital human models" @default.
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- W2044170856 doi "https://doi.org/10.1016/j.cad.2010.11.009" @default.
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