The effect of aging on decision-making while driving: A diffusion model analysis.

Abstract

We present a diffusion model analysis of the effect of aging on decision processes during driving. Our goal was to examine the changes in the underlying components as a function of age and both task and environment difficulty. Younger and older adults performed each of three decision-making tasks while operating a computer-based driving simulator in which the task required a driving action. The first task was a one-choice task in which the response to brake lights turning on was to drive around a lead car. The second and third tasks were two-choice brightness-discrimination tasks in which participants were asked to drive the car to the left/right if there were more black/white pixels in an array of black and white pixels. Results showed that older adults were slower in the one-choice task and made more errors in the two-choice tasks than younger adults. The behavioral data were fitted well by one- and two-choice diffusion models, showing lower evidence accumulation rates (drift rates) in older than younger adults. Moreover, in the two-choice tasks under higher environmental demands, older adults showed a lower decision criterion (boundary separation) to compensate for a slower decision process. Together, the differences we found in the decision components between age groups provided an example of a subtle interaction between speed and accuracy in older versus younger adults, and this demonstrates the utility of this modeling approach in studying age effects in driving.

Reexamining the effects of speed–accuracy instructions with a diffusion-model-based analysis.

“…Understanding how different levels of speed-accuracy stress affect processing can be important in practical situations in which speed is stressed externally, such as driving. Ratcliff and Vanunu (2022) studied older and young adults who were tested while Note. Fits used the hierarchical HDDM method with fits for the speed conditions and the accuracy conditions combined.…”

“…Understanding how different levels of speed–accuracy stress affect processing can be important in practical situations in which speed is stressed externally, such as driving. Ratcliff and Vanunu (2022) studied older and young adults who were tested while performing simulated driving in a personal computer-based driving simulator. As they were driving, a patch of black and white pixels was displayed on the back of a pace car they were following and they were to swerve right if there were more white pixels in the patch and left if there were more black.…”

A drift diffusion model analysis of age-related impact on multisensory decision-making processes

“…Given our environment is inherently multisensory, and most of, if not all, speeded paradigms require a rapid decision to be facilitated based on immediately presented stimuli 13 , 16 , 17 , it is important to consider multisensory integration an integral component of perceptual decision-making 18 , particularly in ageing research where the reliability of incoming (multi)sensory information can be impacted by variations in task difficulty 13 , 15 , 19 . For example, whereas it has been demonstrated that older adults manifest age-related decrements in perceptual decision-making and attentional engagement under higher levels of task difficulty, or reduced perceptual sensitivity 20 – 22 , they display preserved multisensory benefits from integrating unisensory signals that are less coherent and therefore increasingly difficult to consolidate separately 10 , 12 , 23 . By considering the impact of ageing on the interplay between multisensory integration and perceptual decision-making, as well as understanding the modulatory influence of task difficulty within this interplay, we can begin to understand whether multisensory decision-making processes remain preserved or degraded across the adult lifespan.…”