Considering that air conditioning is widely applied for improving human standard of living, this present investigation is focused on the optimization of indoor air quality characteristics of air-conditioned cars using the Gray relational analysis (GRA) and the response surface methodology (RSM). The air-conditioned space is selected and the experiments are planned as per experimental design to study the effects of human load, fresh air supply, and air velocity on human comfort conditions. Mathematical models are developed to predict the comfort conditions, namely temperature, $CO_2$ level, and relative humidity over a specified range of input conditions. The optimum values of comfort conditions for varying input conditions are found by assigning weightages to individual responses using GRA and RSM.