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ORCID
https://orcid.org/0000-0002-7370-2949
Access Type
Campus-Only Access for Five (5) Years
Document Type
thesis
Degree Program
Industrial Engineering & Operations Research
Degree Type
Master of Science in Industrial Engineering and Operations Research (M.S.I.E.O.R.)
Year Degree Awarded
2019
Month Degree Awarded
May
Abstract
The current driving simulator study investigates the effect of 2 distinct levels of distraction on a drivers’ situational awareness and latent and inherent hazard anticipation. In this study, rear-end crashes were used as the primary crash configuration to target a specific category of crashes due to distraction. The two types of task load used in the experiment was a cognitive distraction (mock cell-phone task) & visual distraction (I-pad task). Forty-eight young participants aged 18-25 years navigated 8 scenarios each in a mixed subject design with task load (cognitive or visual distraction) as a between-subject variable and the presence/absence of distraction representing the within-subject variable. All participants drove 4 scenarios with a distraction and 4 scenarios without any distraction. Physiological variables in the form of Heart rate and heart rate variability was collected for each participant during the practice drives and after each of the 8 experimental drives. After the completion of each experimental drive, participants were asked to fill up a NASA TLX questionnaire which quantifies the overall task load experienced by giving it a score between 1 and 100, where higher scores translate to higher perceived task load. Eye-movements were also recorded for the proportion of latent and inherent hazards anticipated and mitigated for all participants. Standard vehicle data (velocity, acceleration & lane offset) were also collected from the simulator for each participants’ each drive. Analysis of data showed that there was a significant difference in velocity, lane offset and task load index scores across the 2 groups (between-subject factors). The vehicle data, heart rate data and TLX data was analyzed using Mixed subject ANOVA. There was also a logistic regression model devised which showed significant effects of velocity, lane offset, TLX scores and age on a participants’ hazard anticipation abilities. The findings have a major practical implication in reducing drivers’ risk of fatal, serious or near crashes.
DOI
https://doi.org/10.7275/14223969
First Advisor
Siby Samuel
Second Advisor
Michael Knodler Jr.
Third Advisor
Shannon Roberts
Recommended Citation
Nair, Rajiv, "Effects of Task Load on Situational Awareness During Rear-End Crash Scenarios - A Simulator Study" (2019). Masters Theses. 791.
https://doi.org/10.7275/14223969
https://scholarworks.umass.edu/masters_theses_2/791