|GABRIELLI ALESSANDRO||Cycle: XXXII |
Section: Computer Science and Engineering
Tutor: BASCETTA LUCA
Advisor: MATTEUCCI MATTEO Major Research topic
:Improving user acceptance in autonomous drivingAbstract:
The car’s automation technology is progressing fast and has already reached a very good level of safety. Because of the advantages that autonomous cars will introduce, the question of how a driver wants to be driven becomes more and more important to ensure driving comfort for the passive driver and, so, fast and wide acceptance and usage of this technology.
The i.Drive Lab, where this research was conducted, aims at developing inter-disciplinary proficiency required for the analysis and modeling of behavioral aspects due to the interaction between driver, vehicle, infrastructure, and environment.
In this research, we have developed a software and hardware platform that allows studying, in a real car, the interaction between driver and car, focusing on the driver stress and the driving factors that impact on driver stress, to increase the little available knowledge in this field and help the acceptance of the car automation in the future. To collect a continuous and objective stress measure, we have used the physiological signals from which it is possible to extract different stress indexes.
We have conducted a validation and preliminary study using our platform on real drivers in both manual and autonomous drive. Results suggest that longitudinal acceleration in both braking and acceleration phase, jerk, and angular velocity have a high correlation with the increasing of the phasic component of the skin conductance that is a very reliable stress index. We also find a high correlation when the car stops to a crossroad or a stop sign with the stress index LF/HF extract from the electrocardiogram.