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Transportation system is at the brink of revolution and many new ways of mobility are arising in the market to ease the pressure on the established transportation infrastructure. Many companies and governments around the world are exploring innovative options in the space of shared mobility to reduce the overall carbon footprint. To expedite the adoption of shared mobility in India, it is necessary to make such options comfortable and cost-effective. One of the most effective way to make shared mobility options cost effective is to comfortably increase occupancy per vehicle footprint. This paper aims to evaluate a novel method of occupant seating to identify the maximum number of passengers a vehicle can accommodate without significant impact on occupant comfort. It is assumed that shared mobility options are used for a short duration of commute, and hence the comfort of the seat can be marginally compromised to increase the total number of occupants.

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.