Comparing the Effects of Traffic Speed and Driver Assistance on Different Age Groups: Mixed Methods User Testing

Although much research exists investigating preferences towards transportation and driver assistance technologies, there is a gap in the literature related to taking a mixed methods approach investigating age-related differences in traffic management behaviors. Previous studies have established that older adults tend to avoid higher risk traffic situations more often than younger adults. This research builds on existing work that compares different aged participants simulated driving behaviors, self-reported workload, and interview responses. Benefits from this study include adding to our understanding of gap maintenance behavior, perceived workload at varying traffic speeds, and preferences among younger and older drivers towards offloading driving tasks to automation. This study assessed younger and older adults driving performance at various levels of simulated traffic both with and without driver assistance technologies. The effects of age group, traffic speed, and assistance level were assessed regarding their impact on gap maintenance behavior, self-reported workload, and interview responses. Driving behavior results from this study found significant differences in minimum headway gap distance and minimum time to collision by age group, traffic speed, and assistance level. Workload results from this study found that multiple NASA Task Load Index items showed a significant difference according to the age group, traffic speed, and assistance level conditions. Lastly, trends in the interview data for different age groups found that younger adults tended to report greater ease of use with the ADAS, while older adults reported higher levels of traffic avoidance, and were less willing to offload driving tasks to an ADAS.

Publication Details

Journal
TigerPrints (Clemson University)
Published
2024-12-01
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

Comparing the Effects of Traffic Speed and Driver Assistance on Different Age Groups: Mixed Methods User Testing

TigerPrints (Clemson University)
Human-Automation Interaction and Safety
article

Comparing the Effects of Traffic Speed and Driver Assistance on Different Age Groups: Mixed Methods User Testing

article en

Abstract

Although much research exists investigating preferences towards transportation and driver assistance technologies, there is a gap in the literature related to taking a mixed methods approach investigating age-related differences in traffic management behaviors. Previous studies have established that older adults tend to avoid higher risk traffic situations more often than younger adults. This research builds on existing work that compares different aged participants simulated driving behaviors, self-reported workload, and interview responses. Benefits from this study include adding to our understanding of gap maintenance behavior, perceived workload at varying traffic speeds, and preferences among younger and older drivers towards offloading driving tasks to automation. This study assessed younger and older adults driving performance at various levels of simulated traffic both with and without driver assistance technologies. The effects of age group, traffic speed, and assistance level were assessed regarding their impact on gap maintenance behavior, self-reported workload, and interview responses. Driving behavior results from this study found significant differences in minimum headway gap distance and minimum time to collision by age group, traffic speed, and assistance level. Workload results from this study found that multiple NASA Task Load Index items showed a significant difference according to the age group, traffic speed, and assistance level conditions. Lastly, trends in the interview data for different age groups found that younger adults tended to report greater ease of use with the ADAS, while older adults reported higher levels of traffic avoidance, and were less willing to offload driving tasks to an ADAS.

TigerPrints (Clemson University)
Openalex Percentile: Top 43%
Human-Automation Interaction and Safety
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