ZF says it is working with neuroscientists from Germany’s Saarland region to put the human at the centre of its technology and avoid motion sickness, which can typically induce dizziness, headaches and nausea on long journeys.

“What does it mean, human-centred, what does it mean for ZF?” said ZF human-centred development project head, Florian Dauth at the supplier’s recent Technology Day in the Eastern Germany city of Dresden. “We can’t only deal with the vehicle itself or the components. We need to integrate the human and need to understand what is motion sickness or discomfort.

“With neural scientists we are gathering a lot of data and to make future function development in terms of AI. Our research said around 60% of passengers are feeling motion sick or have early symptoms. The issue will become more relevant for the whole automotive industry.

“Symptoms are pallor, cold sweating and nausea. ZF as a technology company takes this issue seriously – it is a sensory mismatch and conflict. We want to make our products and functions ready by using information within our algorithms. We use a dynamic driving map so the vehicle stays within boundaries, like manoeuvre or trajectory control.

“That is the main thing to avoid motion sickness, by driving to avoid it. It is teaching [your] car how you want to be driven.”

The scientific basis for the concept is derived by test candidate studies conducted jointly by the Systems Neuroscience & Neurotechnology Unit (SNNU) at Saarland University and HTW Saar. In the studies, 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,” added SNNU director, Daniel Strauss.

“The respective skill sets of the partners complement one another in the context of this collaborative project. The scientific results obtained to date have been very well received by the international specialist community.”

Motion sickness is caused by a discrepancy in perception: The balance organ in the inner ear senses a movement which 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 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, researchers at ZF and SNNU analysed physiological markers which 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.

“Our Motion Sickness Research Vehicle enables us, with the help of a high performance computing platform, to record the large number of physiological measuring data, camera data and measurements relating to driving dynamics,” added Dauth.” At the same time, the vehicle serves as a platform for the development and validation of algorithms.”

During more than 10,000km, the team of researchers gathered 50,000 gigabytes of physiological markers in the central and autonomous nervous system in the form of thermographics, imagery and driving dynamic data.

“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”, said Dauth.

Research currently employs a set of sensors inside the vehicle and wearables for non-invasive measurement. “The challenge is to develop an automotive-compatible system that, over the number of evolutionary steps, enables motion sickness to be detected without physical contact,” noted Dauth.

“We view this as a crucial information to gain a firm grasp of the very individual phenomenon known as motion sickness.”

With this, the driver – or at some later point the control system running the 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. Passengers react differently to vehicle movements and possesses an individual sense of ride comfort.

At ZF, this fact is depicted in an algorithm based on Artificial Intelligence methods, which acquire knowledge of the physical reactions of each passenger, enabling a personalised profile to be created.

As a consequence, individual data are obtained for every passenger in a vehicle, meaning automated vehicles would be able to store the preferred driving style of each passenger.