Personalized Driver Workload Estimation in Real-World Driving Univ of Michigan

Format:

Conference/Event

Author/Creator:

Murphey, Murphey, author.

Contributor:

Kochhar, Dev S.

Xie, Yongquan

Conference Name:

WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2018

Summary:

AbstractDrivers often engage in secondary in-vehicle activity that is not related to vehicle control. This may be functional and/or to relieve monotony. Regardless, drivers believe they can safely do so when their perceived workload is low. In this paper, we describe a data acquisition system and machine learning based algorithms to determine perceived workload. Data collected were from on-road driving in light and heavy traffic, and individual physiological measures were recorded while the driver also performed in-vehicle tasks. Initial results show how the workload function can be personalized to an individual, and what implications this may have for vehicle design

Notes:

Vendor supplied data

Publisher Number:

2018-01-0511

Access Restriction:

Restricted for use by site license