In-Vehicle Technology Use and Associated Factors Among Older Drivers
This study examines the prevalence and frequency of use of in-vehicle technologies as well as the relationships between technology-use frequency and associated factors among a subset of AAA Longitudinal Research on Aging Drivers (AAA LongROAD) participants.
January 2023
Abstract
Introduction
Previous research using data from the AAA LongROAD study has shown that many older drivers use available in-vehicle technologies infrequently, which may limit their safety and mobility benefits. This study examines the prevalence and frequency of use of in-vehicle technologies among a subset of AAA LongROAD participants as well as the relationships between technology-use frequency and perceived cognitive and physical function, driving-related abilities, self-reported driving behaviors, and other measures.
Key Findings
As shown in the table below, the most prevalent in-vehicle technology was integrated Bluetooth cell phone, which 94% of participants reported having, followed by navigation assistance at 60%. In contrast, 5% had semi-autonomous parking assist in their vehicles, and only 3% of participants had night vision enhancement.
Results indicated participants tended to use in-vehicle technologies that alert them of unsafe driving situations (e.g., forward collision warning, blind spot warning) more often than those having other primary functionality (e.g., taking actions to assist drivers’ vehicle operations, providing services or information). In general, greater self-reported cognitive concerns and driving avoidance behaviors in challenging situations were significantly associated with lower use of some technologies. Additionally, greater reported physical function, driving comfort, perceived driving-related abilities, and driving space were associated with higher use of some technologies. Meanwhile, the associations with self-reported driving safety measures (i.e., number of crashes, driving errors, lapses, and violations) were not significant.
Presence and frequency of use of in-vehicle technologies (n=324)
| Primary Functionality | Technology | Prevalence:
n (%) |
Average Frequency of Use*
(Standard Deviation) |
| Technologies that alert drivers to unsafe driving situations; drivers must take action to mitigate potential hazards | Forward Collision Warning | 72 (22.22%) | 4.42 (1.28) |
| Blind Spot Warning | 61 (18.83%) | 4.67 (0.98) | |
| Lane Departure Warning | 96 (29.63%) | 4.10 (1.44) | |
| Technologies that take action to assist drivers with vehicle operations | Adaptive Cruise Control | 131 (40.43%) | 3.04 (1.33) |
| Semi-Autonomous Parking Assist | 17 (5.25%) | 2.35 (1.54) | |
| Technologies intended to support drivers for safe vehicle operations | Fatigue/Drowsy Driving Alert | 15 (4.63%) | 3.93 (1.58) |
| Night Vision Enhancement | 11 (3.40%) | 3.36 (1.58) | |
| Types of technologies intended to support drivers with services or information | Navigation Assistance | 194 (59.88%) | 3.20 (1.55) |
| Voice Control | 161 (49.69%) | 2.34 (1.38) | |
| Integrated Bluetooth Cell Phone | 306 (94.44%) | 3.08 (1.60) | |
| In-Vehicle Concierge | 70 (21.60%) | 1.60 (0.77) |
* Frequency of use scale: 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always.
Methodology
Data for this study are from the AAA LongROAD study, a multi-site prospective cohort study designed to collect data on the health, behavioral, environmental, and vehicle technology factors influencing older adults’ driving and safety. The present study used data collected from the Year 3 follow-up (June 28, 2018–May 20, 2020), which consisted of a telephone interview during which a series of questionnaires were administered regarding participants’ driving, health, functioning, and primary vehicles.
Descriptive analyses were conducted to examine prevalence and frequency of use of the in-vehicle technologies. A Spearman correlation (rs) matrix was constructed to assess the associations between the in-vehicle technology-use frequency and the health and other driving-related variables.
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