VDM - Vehicle Driver Monitoring

Research Group:


Status:

active

Start date:

2013-04-01

End date:

2017-03-31

The VDM project aims to provide tools for development of safety systems including a basis for continuously monitoring driver’s state and based on these, carry out suitable counter measurements to prevent/reduce accidents. It will develop state of the art knowledge in the area of physiological measuring and analysis, strengthen the competitiveness of the Swedish automotive industry and provide tools for development of active safety systems. The participants in the project have extensive experience of studying different driver states and human monitoring e.g. of research on mental load, sleepiness and advanced analysis methods. In the VDM project this will be brought together in a general research framework and a mental-load model, using physiological measures as indicators. The results of the VDM project will provide a basis for future research and development in the field of driver states.

[Show all publications]

Distributed Multivariate Physiological Signal Analytics for Drivers’ Mental State Monitoring (Oct 2017)
Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
4th EAI International Conference on IoT Technologies for HealthCare (HealthyIOT'17)

Vehicle Driver Monitoring: sleepiness and cognitive load (May 2017)
Emma Nilsson , Christer Ahlström , Shaibal Barua, Carina Fors , Per Lindén , Bo Svanberg , Shahina Begum, Mobyen Uddin Ahmed, Anna Anund
Swedish National Road and Transport Research Institute (VTI) (VTI rapport 937A)

Classifying drivers’ cognitive load using EEG signals (May 2017)
Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
14th International Conference on Wearable, micro & Nano Technologies (pHealth2017)

Driver’s State Monitoring: A Case Study on Big Data Analytics (Oct 2016)
Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed
The 3rd EAI International Conference on IoT Technologies for HealthCare (HealthyIoT'16)

AUTOMATED EEG ARTIFACTS HANDLING FOR DRIVER SLEEPINESS MONITORING (Feb 2016)
Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed, Christer Ahlström
2nd International Symposium on Somnolence, Vigilance, and Safety (SomnoSafe2016)

Clustering based Approach for Automated EEG Artifacts Handling (Nov 2015)
Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed
The 13th Scandinavian Conference on Artificial Intelligence (SCAI 2015)

Shahina Begum, Associate Professor

Email: shahina.begum@mdh.se
Room: U1-131
Phone: +46-21-107370