An exploration of the role of driving experience on self-reported and real-world aberrant driving behaviors

"Regulating my anxiety worsens the safety of my driving": The synergistic influence of spatial anxiety and Self-regulation on driving behavior

Spatial Anxiety (SA) can be defined as the fear and apprehension experienced during tasks that require spatial thinking and may negatively impact the execution of daily actions. Although it has been explored in several research fields, limited research has explored the effects of SA on specific driving behaviours. In the current study, it was hypothesised that the severity of SA affects risky driving behaviours, and that this relationship is mediated by the driver's self-regulation abilities. Self-reported SA symptoms, driving self-regulation abilities, and risky driving behaviours (i.e., errors, violations, and lapses) were examined in 838 Italian drivers. Data were analysed through linear regressions and path analysis models, controlling for sociodemographic variables. The results showed the negative effects of SA on driving errors and lapses. As hypothesised, a driver's self-regulation abilities mediated the influence of SA on driving lapses, but not on errors nor violations. These findings suggest that the inclination to self-regulate the SA experienced while driving contribute to increase the occurrence of driving lapses. Showing specific pathways through which SA impacts risky driving, these results provide valuable insights for the development of 'driver-focused' road safety interventions.

Validating self-reported driving behaviours as determinants of real-world driving speeds

Self-reported driver behaviour has long been a tool used by road safety researchers to classify drivers and to evaluate the impact of interventions yet the relationship with real-world driving is challenging to validate due to the need for extensive, detailed observations of normal driving. This study examines this association by applying the large UDRIVE naturalistic driving study data involving 96 car drivers, comprising 131,462 trips and 1,459,110 km travelled over a duration of 32,096 hours, to compare individual questions and composite indicators based on the Driver Behaviour Questionnaire with real world driving. Self-reported speed behaviour was compared to the measured values under urban and highway conditions. Generalised Linear Mixed Models were developed to examine the relationships between the observed speed behaviours with DBQ errors and violations scores in conjunction with traffic and environmental factors. Drivers' self-reported data on speed selection seldom aligned with their real-world behaviour and there were no meaningful differences between many of the response categories. The DBQ violations and errors scales showed a highly significant correlation with driving speed indicators however they had a low explanatory power compared to other traffic situational and driving factors. Overall, the study highlights the need to validate self-reported driving data against the accuracy and relevance to real-world driving.

Is driving experience all that matters? Drivers' takeover performance in conditionally automated driving

INTRODUCTION

In conditionally automated driving, drivers are allowed to engage in non-driving related tasks (NDRTs) and are occasionally requested to take over vehicle control in situations that the automation system cannot handle. Drivers may not be able to adequately perform such requests if they have limited driving experience. This study investigates the influence of driving experience on takeover performance in conditionally automated driving.

METHOD

Nineteen subjects participated in this driving simulator study. The NDRTs consisted of three tasks: writing business emails (working condition), watching videos (entertaining condition), and taking a break with eyes closed (resting condition). These three NDRTs require drivers to invest high, moderate, and low levels of mental workload, respectively. The duration of engagement in each NDRT before a takeover request (TOR) was either 5 minutes (short interval) or 30 minutes (long interval).

RESULTS

Drivers' driving experience and performance during the control period are highly correlated with their TOR performance. Furthermore, the type and duration of NDRT influence TOR performance, and inexperienced drivers exhibit poorer TOR performance than experienced drivers.

CONCLUSIONS AND PRACTICAL APPLICATIONS

These findings have relevance for the types of NDRTs that ought to be permitted during automated driving, the design of automated driving systems, and the formulation of regulations regarding the responsible use of automated vehicles.