The development of autonomous vehicles is rapidly moving forward through significant efforts from the automotive industry and researchers. The design and the usage of the vehicles can drastically change, leading to a transformation of the vehicle-transport system. One key enabler for the complete success of autonomous vehicles is to design and control the vehicle so that the passengers do not become motion sick. There is therefore a need to investigate what causes motion sickness and how motion sickness can be evaluated. This includes the medical understanding of what is causing motion sickness to understand the human aspects of a range of motion-related parameters such as accelerations, vibrations, etc. Furthermore, with the help of modelling detect and predict motion sickness. There exist today different models to predict and evaluate motion sickness, but they are often rather limited and not directly usable as tools in the vehicle development process. There are both empirical and theoretical approaches used in the modelling of motion sickness, which have different advantages and disadvantages to each other. In this paper, the causes of motion sickness and some existing motion sickness models will be discussed. With the help of identified motion sickness prediction models, new technical innovations needed within vehicle dynamics control and motion planning control can be developed to minimise the risk of motion sickness in autonomous vehicles. Motion sickness prediction models are important tools in the early design stage of development on how to control and design autonomous vehicles so that the functional conflict between safety, comfort and performance is handled for the complete success of autonomous vehicles when it comes to economic and social benefits.