Search

Objective There is an established relationship in the literature between cognitive function and driving performance in older drivers and new evidence suggests that this relationship also exists in younger drivers. Given this, it follows that this relationship may exist for all drivers, however the relationship between cognitive function and driving in drivers in middle adulthood has not yet been examined. The current study therefore aims to examine this relationship of overall cognitive function and driving, as well as the individual cognitive domains relevant to driving for drivers in middle adulthood. Method The participants were 89 drivers aged between 25 and 65 years. Each participant was assessed on a battery of cognitive tests and completed a drive on a driving simulator. Measures of driving performance included speeding, lane deviation, and an overall driving performance score. Results The results showed new evidence to suggest overall cognitive function can predict speeding and overall driving performance. In addition, the cognitive domains of mental status, executive function and memory were found to be significant individual predictors in this cohort. Conclusions Taken together with previous findings, this study provides evidence to suggest that cognitive function is important to driving across the lifespan. The generalisability of the current results are limited due to the majority of participants being from a university sample, therefore these findings will need to be replicated in a more representative sample. Future research should focus on the development of a comprehensive model to explain driving performance across all ages and across traffic psychology disciplines.

Public acceptability of automated vehicles (AVs) is critical to gauge in order to understand the factors that are likely to encourage drivers to utilise the technology and realise its predicted safety and other benefits. Willingness to pay (WTP) is a particularly important facet of acceptability as AVs will only penetrate the market in so much as people are willing to purchase it. However, there currently exists a lack of research that has examined how attitudes and opinions towards AVs may impact WTP for the technology. Therefore, the aim of this study was to test the predictive utility of AV-related attitudes and opinions in identifying individuals who are, and those who are not, willing to pay for the technology. The study employed a sample of 6133 Australian and New Zealand respondents who responded to a comprehensive online survey (including over 50 items specific targeting aspects of AV acceptability). Survey items gauged attitudes and opinions closely related to the acceptability of AVs including (but not limited to) (a) perceived benefits and concerns, (b) likely conditions of use, (c) engagement in secondary activities when supported by automation, and (d) WTP for the technology. Results showed that attitudes and opinions relating to perceived benefits, level of comfort with an AV undertaking certain driving functions, and engagement in secondary activities were among the strongest predictors of WTP, over and above key sociodemographic variables (e.g., age, salary), while the weakest were associated with awareness of AV technologies and perceived concerns. As such, the study makes a novel contribution to the existing literature by highlighting specific attitudes and opinions that may be crucial to consider when attempting to better understand, and predict, peoples’ WTP for AV technology prior to system use. Given this, we believe the information derived from this study will be useful for industry and government stakeholders.