Online Program Home
My Program

Abstract Details

Activity Number: 89 - SPEED: Survey Methods, Transportation Studies, SocioEconomics, and General Statistical Methods Part 2
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 5:05 PM to 5:50 PM
Sponsor: Transportation Statistics Interest Group
Abstract #307922
Title: The Relationship Between Driver Performance and Driver Workload Using Functional Data Analysis
Author(s): Jundi Liu* and Erika Miller and Linda Ng Boyle
Companies: University of Washington and Colorado State University and University of Washington
Keywords: Functional Data Analysis; Functional Principal Component Analysis; On-road study; Driver behavior; Driver workload

Traffic environments have a significant impact on driver cognitive workload. Driving through enclosed tunnels can negatively impact the driver’s workload as well as driving performance. An on-road study was conducted on an interstate route that included tunnel and non-tunnel segments. The study included physiological measurements (heart rate variability) and driving performance measures (vehicle speed, braking). These high-frequency measures have smooth transitions over time, and can be examined using functional data analysis (FDA), to identify relationships between mean space-speed profiles and heart rate variability over different road segments. Functional principal component analysis (FPCA) is also used to extract the components that characterize the driver behavior in the tunnel segments. The results can provide important suggestions for future road and tunnel designs.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program