This paper discuss about existing mathematical models for in-cabin CO₂ concentrations and compare it with experimentally measured CO₂ concentration. The study involves with different size light passenger vehicles under different occupancy and airflow conditions. The sensor board measures temperature, humidity and atmospheric gas concentrations at front and rear of the cabin during journey and these data are used to compare with the theoretical model predicted values. The recirculation mode made rice in CO₂ levels more rapidly compared to open air intake through vehicle air conditioning system. However, the open air intake mode is more vulnerable to toxic gases inside tunnels and confined environments. Therefore measuring in cabin carbon dioxide and oxygen levels and opening ventilation intelligently is essential in the driver-less future vehicles. This study pays the path for intelligent control of cabin air depending on the external environment the vehicle being passing through and the present cabin air quality. New algorithms for predicting in cabin air quality will be derived through experimental observations.