Citation

Jan MT, Moshfeghi S, Conniff J, Jang J, Yang K, Zhai J, Rosselli M, Newman D, Tappen R, Furht B. Proc. Int. Conf. Comput. Sci. Comput. Intell. 2022; 2022: 1269-1273.

Copyright

(Copyright © 2022, IEEE Computer Society Conference Publishing Services)

DOI

10.1109/csci58124.2022.00228

PMID

38486660

PMCID

PMC10939046

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.

Language: en

Keywords

driver’s behavior; in-vehicle cameras; in-vehicle sensing; telematics sensors