Understanding and sensing human conditions that affect driver performance and satisfaction
In any autonomous driving scenario, the driver remains central to the overall process. It is important to understand the driver’s physiological and psychological states, their intent and their driving task and context, in order to assess whether the driver is attentive and capable to take over control of the vehicle. The vision for the future of driving and the ageing population is that humans will want to maintain autonomy and the will to drive. Technology can give drivers the confidence to continue to enjoy driving knowing that the car’s co-pilot will intervene if help is needed.It is anticipated that avoiding or reducing accidents will give assurance and confidence to the driver. ADAPT sought to assess emotional and physical states while driving using sensors mixed with AI.
Using existing literature, TILDA datasets on aging populations, and research in sensors and AI, ADAPT identified all conditions (medical conditions, medications, substances) significantly associated with increased crash risk and developed a socio-technical system linking driver conditions and interpretation challenges.
We developed a Co-pilot (Car) data gathering and interpretation framework and sensor network for Driver Estimation to estimate the drivers physical and psychological state to help improve driving safety and satisfaction
Future co-pilot/driver partnership concept
Current and future use of in-car sensors
Future possible use of AI to assess driver conditions
Develop an advantage in the aging community to maintain the desire and confidence to drive
Develop an in-car diagnosis system
Want to learn about commercialising university research? @TrinityResInnov Neil Gordon will speak at our next #webinar on 27th July at 10am. Register online: https://bit.ly/3B01914LI