© 2025 All rights reserved
Problem statement
The client wanted to make a vehicle UX that showcases AIML learning your behaviour and then functioning proactively to assist the driver and make driving safer and more fun.
Customer research
We carried out a qualitative and quantitive research project on hundreds of users around the world to find out amongst other things:
Their major painpoints
Preferences for infotainment
How vehicles are used alone and with passengers
Human Factors strategy
The interaction logic for the vehicle was a critical factor to establish where software activity was to be surfaced to the user.
Eyes on the road and speed of action were the critical elements governing the experience.
A UX ruleset was created to define where interactions would surface in the HMI.
Design prototyping
The experience flow and interactions for the product was crafted and prototyped in card, on the bench and then digitally.
My team built a fully driveable simulator to enable us to test new UX on real users in the safety of the lab, before deploying to the development team for integration to the vehicle.
Testing with customers
We worked with our software engineers to create a fully mature and operational machine-learning framework and in-vehicle HMI.
This MVP was then tested with end-users through focus-groups in Japan, the US and Europe.
The product was iteratively modified to improve the experience.
Selling to OEM customers
The vehicles were handed over to Sales and Product teams and have been demonstrated to many vehicle OEMs on premises and at trade shows around the world.
© 2025 All rights reserved