Digital human models have greatly enhanced design for the automotive environment. The major advantage of the models 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 in to it. This study enhances the postures and there seating layout for occupants considering their most comfortable position. While all the Occupants are accommodated to their respective positions which finally can be stacked up for space assessments. Understanding the usage patterns of users with respect to seating will have huge impact on setting the target for overall vehicle size, including the vehicle length and luggage compartment. SAE recommended practices including SAE J1517 and SAE J4004 predicting the driver-selected seat position based on the USA population. Similar prediction of driver selected seating position for Indian population does not exist. Premananth et al. (SAE Technical Paper 2016-01-1431) suggests that a correction factor is required over prediction model of SAE J4004 and SAE J1517 to encompass the diversity found in Indian population. Therefore, it becomes vital to examine the same scenarios either by user trails/clinics or by digital simulation for Indian population. This paper explores and proves the ways in which vehicle spaciousness can be quantified and explores new possibilities based on customer seating positions in Digital environment using DHMs. This improves the package efficiency and the occupant comfort seating posture requirements which allows the engineers to maximize the interior space for a given exterior length of the vehicle or vice versa.