The reports below present a preliminary investigation into the “Smart Mobility” challenge. The end vision of the project was to use the rich data set available from Ford vehicles, plus external data, to generate consumer “insights” that encouraged safer, more aware, and more efficient drivers within urban and non-urban environments.
Our study focussed on four key elements to enable this vision:
1. Data analytic techniques aiming to produce algorithms for real time in vehicle data
processing to classify journeys;
2. Driver experience feedback and engagement around journeys by the study of language
use within regularly kept driving diaries;
3. Relationship of vehicle measures to cognitive state investigated through a simulated
drive with eye tracking and brain activity recording;
4. User experience design exploration.
The results are provided in the reports below, and are extremely promising. They indicate that in-vehicle journey and driver analytics, even using only existing sensors, have the ability to indicate driver cognitive state and experience.
As is common in research, the answers obtained introduce new questions and the initial work needs to be followed up with larger scale studies. However, with the insights gained already, we can produce some recommendations for next steps.
Please read the reports below for full information:
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Horizon Digital Economy Research, University of
Nottingham Innovation Park, Triumph Road, Nottingham,
NG7 2TU
horizon@nottingham.ac.uk
