Summer car journeys can be synonymous with dizziness, headaches, and nausea. Children are especially prone to motion sickness. ZF is working together with neuro-technologists from Germany’s Saarland region to investigate how to detect motion sickness at an early stage. This may aid in developing smart driving features to detect symptoms early. Thereby, ZF focuses on the comfort of occupants as a decisive factor for next generation mobility.
Just in time for the summer holidays: ZF researches to counteract motion sickness
On long car journeys, few people are immune from motion sickness when seated in the back or in the front passenger seat. About a third of passengers suffer a sense of dizziness and motion sickness which makes any attempt to enjoy the ride, or to work while on the road, difficult or near to impossible.
To help solve this problem, ZF is looking beyond a purely vehicle-based approach: “We are among the very first companies in this sector to place the occupants and their individual driving experience center stage”, states Florian Dauth, responsible for activities in the field of Human Centered Vehicle Motion Control in ZF’s Advanced Technology Development. “Our goal is to identify individual instances of motion sickness and to devise measures that relate to the prevailing condition of the passenger.”
The scientific basis for this concept is derived from test candidate studies that were conducted jointly by the Systems Neuroscience & Neurotechnology Unit (SNNU) at the Saarland University and htw saar. In these studies, the physiological reactions of test candidates were examined in a variety of driving situations.
“Our pioneering research incorporates the fields of neuro-technology, psycho-physiology, artificial intelligence and driving dynamics”, said Prof. Dr. Dr. Daniel J. Strauss, Director of the SNNU. “The respective skill sets of the partners complement one another perfectly in the context of this collaborative project. The scientific results obtained to date have been very well received by the international specialist community.”
Scientific data provides an insight into physiological processes
Motion sickness is caused by a discrepancy in perception: The balance organ in the inner ear senses a movement that is not confirmed by other sense organs such as the eyes. This is most likely to happen when a passenger is concentrating on a screen or a book. In this situation, the human body responds with a reaction that is in many ways similar to the response to poisoning. The symptoms range from a slight sense of unease to acute motion sickness.
In several studies, the researchers at ZF and SNNU analyzed the physiological markers that show the highest correlation with the subjective perception of motion sickness by individuals. They also examined how this correlates to the driving dynamics of a vehicle. Physiological indicators are among other changes in the body such as temperature and galvanic skin response. “Our Motion Sickness Research Vehicle enables us, with the help of a high performance computing platform, to record the large number of physiological and camera data, and measurements relating to driving dynamics. At the same time, the vehicle serves as a platform for the development and validation of algorithms”, explains Dauth.
Over more than ten thousand kilometers, the team of researchers gathered more than fifty thousand gigabytes of physiological markers in the central and autonomous nervous system in the form of thermographics, imagery, and driving dynamic data. In this sector, this is a unique and multi-modal data resource on the subject of motion sickness. “It helps us to apply a scientific procedure to the task of gaining an understanding of the phenomenon of motion sickness, and is at the same time a basis for depicting AI-based algorithms”, states Dauth as he explains the development process.
People as the focal point
The research currently employs a set of sensors inside the vehicle along wearables for non-invasive measurement. “The challenge is to develop an automotive-compatible system that, over a number of evolutionary steps, enables motion sickness to be detected without physical contact. We view this as crucial information to gain a firm grasp of the very individual phenomenon that is known as motion sickness”, states Dauth. With this, the driver – or at some future point, the control system running an automated vehicle – can identify at an early stage if, by way of example, a child on the back seat is starting to feel ill and can adapt driving characteristics accordingly.
The vehicle learns a preventive driving style
Everyone reacts differently to vehicle movements, and possesses an individual sense of ride comfort. At ZF, this fact is depicted in an algorithm based on ArtificiaI Intelligence methods that acquire knowledge of the physical reactions of each passenger, enabling a personalized profile to be created. As a consequence of this, individual data is obtained for every passenger in a vehicle, meaning that automated vehicles would actually be able to store the preferred driving style of each passenger.