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In automotive industry, design of vehicle to end customer with proper ergonomics and balancing the design is always a challenge, for which an accurate prediction of postures are needed. Several studies have used Digital Human Models (DHM) to examine specific movements related to ingress and egress by translating complex tasks, like vehicle egress through DHMs. This requires an in-depth analysis of users to ensure such models reflect the range of abilities inherent to the population. Designers are increasingly using digital mock-ups of the built environment using DHMs as a means to reduce costs and speed-up the “time-to-market” of products. DHMs can help to improve the ergonomics of a product but must be representative of actual users.

Digital human models (DHM) have greatly enhanced design for the automotive environment. The major advantage of the DHMs today is their ability to quickly test a broad range of the population within specific design parameters. The need to create expensive prototypes and run time consuming clinics can be significantly reduced. However, while the anthropometric databases within these models are comprehensive, the ability to position the manikin’s posture is limited and needs lot of optimization. This study enhances the occupant postures and their seating positions, in all instances the occupant was instructed to adjust to the vehicle parameters so they were in their most comfortable position. While all the Occupants are accommodated to their respective positions which finally can be stacked up for space assessments. This paper aims at simulating those scenarios for different percentiles / population which will further aid in decision making for critical parameters.