Methods and Tools for Monitoring Driver's Behavior
Muhammad Tanveer Jan, Sonia Moshfeghi, Joshua William Conniff, Jinwoo Jang, KwangSoo Yang, Jiannan Zhai, Mónica Rosselli, David Newman, Ruth M. Tappen, Borko Furht
Abstract
In-vehicle sensing technology has gained tremendous attention due to its ability to support major technological developments, such as connected vehicles and self-driving cars. In-vehicle sensing data are invaluable and important data sources for traffic management systems. In this paper we propose an innovative architecture of unobtrusive in-vehicle sensors and present methods and tools that are used to measure the behavior of drivers. The proposed architecture including methods and tools are used in our NIH project to monitor and identify older drivers with early dementia.
Topics & Concepts
ArchitectureAdvanced driver assistance systemsComputer scienceMeasure (data warehouse)Systems engineeringEmbedded systemEngineeringTransport engineeringArtificial intelligenceDatabaseArtVisual artsEEG and Brain-Computer InterfacesContext-Aware Activity Recognition SystemsHuman-Automation Interaction and Safety