|Title:||An intelligent system for driver cognitive load detection using eye tracking data|
Vehicle driving requires attention, effort, alertness and quick reactions. Reduced vehicle control due to different mental states can lead to a severe accidents. One factor that affects the driver’s mental state is his/her level of cognitive load. Cognitive load can be defined as effortful and conscious resource allocation within the brain, needed to deal with non-routine or inherently difficult tasks, resulting in controlled performance.
Humans have limited capacity for cognitive load and engaging in one cognitively loading task interferes with one’s ability to at the same time engage in other cognitively loading task. Performing cognitively loading secondary tasks, such as talking on the phone, while driving can hence affect the performance in the primary task, i.e. the driving.
In the last few years, eye tracking has become a non-invasive method for driver cognitive load detection and analysis. Measures such as pupil diameter and gaze concentration have been shown to correlate with level of cognitive load. Factors such as ambient light and traffic environment also have a great effect on those measures though, making interpretation of them difficult in applied settings.
This thesis project aims to develop an intelligent system for driver cognitive load detection using eye-tracking data. It also requires investigation of eye-tracking data that have been collected in a simulator study for driver cognitive load detection and analysis.
The project work can be subdivided as follows:
1. Literature study and survey of existing methods and systems
2. Data analysis
3. Development of an intelligent system using machine learning algorithm
4. System evaluation
|Prerequisites:||Knowledge in Matlab and machine learning is advantageous|
|IDT supervisors:||Shaibal Barua|
|Examiner:||Mobyen Uddin Ahmed|
|Comments:||The thesis is within the VDM project and data is protected by the PUL and data sharing contract. Same PUL and data sharing contract will be applied for students who will work on this thesis.|
|Company contact:||Volvo Car Emma Nilsson firstname.lastname@example.org|