Prediction of In-Vehicle Reach Surfaces and Discomfort by Digital Human Models

Recently, we proposed a unified data based approach which aimed at predicting both reach envelopes and reach discomfort for a digital human model [1]. In this approach, four reach surfaces, from half-flexed arm distance to maximum reach with torso participation, need to be defined. The discomfort associated with a point on each surface is defined at first. Then, the discomfort of an intermediate distance between two reach distances is interpolated. The proposed approach was demonstrated on a reaching task corresponding to push a toggle switch from a seated posture without seat back. As data were collected in an environment which is different from the driving situation, these data can not be directly applied to driver's reach capacity and discomfort. In this study, we will apply this approach for in-car driver's reach for predicting different reach envelopes and discomfort.