It is anticipated that for the automated driving industry to grow, public acceptance is required. The trust and acceptance of automated vehicles are primarily dependent on the travelling experience of people. In automated vehicles, passengers are expected to be engaged in non-driving tasks that are likely to decrease their predictability of the vehicle manoeuvre. This would greatly increase their sensitivity to motion sickness, which a large population already suffers in manual driving. Developing a control algorithm to reduce motion sickness in automated vehicles is an absolute necessity. In this research, first, a novel method is proposed to design a test road profile. Next, the study presents an optimal control strategy that implements a speed profiling method to minimise Motion Sickness Dose Value (MSDV), suitable for objective evaluation of motion sickness; on the test road. The resulting manoeuvre from the proposed control algorithm is an 'active mode driving.' A time minimisation manoeuvre defined as 'passive mode driving' is also simulated on the same test road to examine the efficiency of the proposed algorithm. For validation, a subjective assessment is carried out with 16 participants using a driving simulator in a comparative study between the two driving modes. Subjective responses are recorded with MIsery SCale (MISC) during the exposure and with a Motion Sickness Assessment Questionnaire (MSAQ) at the end of the experiment. It is found that active mode driving resulted in 38% MSDV reduction than passive mode driving. Further, the mean MISC rating in active mode was 62% lower than passive mode driving.