Activity Number:
|
29
- SPEED: Survey Methods, Transportation Studies, SocioEconomics, and General Statistical Methods Part 1
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Transportation Statistics Interest Group
|
Abstract #304805
|
Presentation
|
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
|
Abstract:
|
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.