Analysis of biometric and automotive data and their relationship with at risk behaviours and near miss accidents
Ref. prof. Roberto Sacile
This research will focus on data analysis techniques to identify at risk behaviours and near miss accidents during driving processes of vehicles on road.
The driving processes will be simulated on a simulation software (OKTAL), but some experiments to validate simulation data will be also developed during true driving sessions. The data to be monitored are coming from the driver (breath rate, electroencephalograph on 8 channels, heart rate, movements as available from actigraph), from the can bus of the vehicle, as well as from other external sources (e.g. weather data, traffic…). The goal of the data analysis is:
- To verify the correspondence between simulated and true driving data
- To verify patterns of data which are related to near-miss accidents or at risk behaviours.
Safety, Driving Simulation, Human Behaviour
Matlab, control techniques, data analysis, programming
Collaborations with external company: Eni