Motion sickness affects over 70% of people. Spencer Salter, wellness technology researcher at JLR said that little has been known about the causes and how to mitigate them.
Now, through its industry-leading motion sickness research, JLR has created an algorithm that generates a ‘wellness score’ for each passenger. This can be used to automatically personalise a vehicle’s driving and cabin settings to reduce the effects of feeling car sick by up to 60%.
JLR has already collected 15,000 miles of motion sickness data and tested the effects caused by performing a task while in transit, such as checking emails. This has enabled the creation of a baseline driving style for self-driving vehicles to work towards, minimising the need for steering corrections and therefore the risk of motion sickness while passengers work or relax.
Salter said: “As we move towards an autonomous future where occupants will have more time to either work, read or relax on longer journeys, it's important we develop vehicles that can adapt to reduce the effects of motion sickness in a way that's tailored to each passenger.”
Motion sickness is often caused when the eyes observe information that is different from what is sensed by the inner ear, skin or body forces – commonly when reading.
The ‘wellness score’ calculates how susceptible individual drivers and passengers are to feeling car sick, using biometric sensors that record physiological signals. Combining this with motion and dynamics data, the vehicle will reliably know when a passenger or driver is becoming motion sick – before they do.
Steve Iley, JLR’s Chief Medical Officer, said: “This research has created a solution that, with its solid scientific foundation, can make travelling enjoyable, regardless of your susceptibility to motion sickness.”
The first phase of the research completes this month. The findings are already being implemented into further projects across research ensuring Jaguar Land Rover can create the ultimate personalised cabin experience for its customers in future vehicles.