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VDMS: Vehicle and Driver Monitoring Systems

Authors:

Mobyen Uddin Ahmed, Bertil Hök

Publication Type:

Conference/Workshop Paper

Venue:

Medicinteknikdagarna 2019


Abstract

Vehicle and driver monitoring systems is divided into two folds, 1) monitoring drivers’ human factor and 2) in-vehicle alcohol sensing. Monitoring drivers’ is based on Human Factor (HF), i.e. distraction, tiredness, stress, under the influence of alcohol, etc. as presented by the European Commission. HF can monitor based on physiological sensor signals i.e. Electroencephalography (EEG), Electrocardiography (ECG), Electrooculography (EOG) and Galvanic Skin Response (GSR), etc. A large variety of machine learning methods have been used for clustering and classification of physiological sensor signals in different types of projects for stress and mental load, i.e. ANN, Dempster–Shafer (D‐S) theory and K‐Nearest Neighbor (KNN) classifier. So, machine learning methods will be applied for advanced signal processing, and classification. In addition, information fusion on the signals (EEG, ECG, SC, etc.) both in sensor level, feature level, and decision level will be investigated. In-vehicle alcohol sensing focusing on drunk driving, is causing 25-30% of road fatalities in Europe and the US, although the fraction of intoxicated drivers is much smaller. In Europe, more than 10 000 deaths occur annually. Alcolocks and other state-of-the-art devices have not been accepted by the general public. Senseair is working on passive in-vehicle alcohol detection in a major international collaborative effort supported by traffic safety authorities in both Sweden and the US, and also including the automotive industry. A major breakthrough was reported in 2017 concerning passive in-vehicle detection of driver breath alcohol using CO2 as a biomarker. The research questions and future challenges related to breath alcohol detection are moving upwards in the system hierarchy from sensor and electronic hardware design towards higher system levels, including intelligent signal processing algorithms, data management and communication using IoT networking, system architecture and machine intelligence.

Bibtex

@inproceedings{Ahmed5624,
author = {Mobyen Uddin Ahmed and Bertil H{\"o}k},
title = {VDMS: Vehicle and Driver Monitoring Systems},
month = {October},
year = {2019},
booktitle = {Medicinteknikdagarna 2019},
url = {http://www.es.mdh.se/publications/5624-}
}