Teaching older drivers to navigate GPS technology

J Safety Res. 2020 Feb:72:165-171. doi: 10.1016/j.jsr.2019.12.001. Epub 2019 Dec 31.

Abstract

Background and objectives: New technologies are being implemented in motor vehicles. One key technology is the electronic navigation system (ENS) that assists the driver in wayfinding, or actually guides the vehicle in higher level automation vehicles. It is unclear how older adults interact with ENSs and the best approach to train older adults to use the devices. The objectives of this study were to explore how older drivers interacted with an ENS while driving on live roadways and how various training approaches impacted older drivers' ability to accurately enter destinations into the ENS.

Research design and methods: In Experiment 1, 80 older drivers navigated unfamiliar routes using an ENS or paper directions and completed a series of ENS destination entry tasks. In Experiment 2, 60 older drivers completed one of three training conditions (ENS video only, ENS video with hands-on training, placebo) to examine the impacts of training on destination entry performance.

Results and discussion: Driving performance was aided by the use of the ENS, but many older drivers had difficulty entering destinations into the device (Experiment 1). The combined video with hands-on ENS training resulted in the best overall destination entry performance (Experiment 2). Practical applications: The results suggest older drivers may experience problems entering destinations into ENSs, but training can improve performance. These performance issues may be especially important as more vehicle features require interaction with computer systems to select destinations or other automation related features. Further research is needed to determine how to prepare the next generation of older drivers who will interact with technologies aimed at increasing mobility.

Keywords: Aging processes; Designing for the elderly; Driver behavior; Navigation; Training evaluation; Vehicle automation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Automobile Driving / education*
  • Female
  • Geographic Information Systems*
  • Humans
  • Male
  • Middle Aged
  • Motor Vehicles*
  • North Carolina
  • Technology