This research aimed to assess the extent to which using a hand-held mobile phone affected young drivers’ (aged 17–25 years) takeback control of a simulated conditional automated vehicle (AV), relative to an auditory working memory n-back task and monitoring the road environment (control condition). In addition to takeback control, this study also applied the Theory of Planned Behaviour (TPB) to assess if there were any differences in future intentions to use AVs after participants had experienced the automated functions of the vehicle compared to pre-drive (baseline). Trust was also measured pre-and post-drive. These additional constructs were included to further assess if the predictors of intentions to use AVs changed after participants had experienced a simulator drive which involve non-driving related tasks (NDRT). Thirty-three young Australian drivers (Mage = 20.97 years, 17 females) took part in the one-hour within groups study which comprised pre-and post-drive self-report questionnaires and operating the CARRS-Q advanced driving simulator. In contrast to previous research on NDRT and takeback control (see Zhang et al., 2019), the results revealed that there were no significant differences in takeback control of the vehicle when drivers were using their hand-held mobile phone compared to completing the working memory n-back task or monitoring the road environment. However, a hierarchical regression revealed that participants reported significantly higher ratings that important others would approve of them using a conditional AV and greater control over whether or not they would intend to use an AV in the future post-drive compared to pre-drive, providing partial support for hypothesis 2. Overall, these findings suggest that using a hand-held mobile phone does not negatively influence young drivers’ takeback control of an AV. Further, the study highlights the influence that important others may have in determining whether young drivers intend to use AVs in the future.@en

Eco-safe driving is a promising approach to improve road safety while reducing transport emissions. The application of an eco-safe driving system is feasible with the support of vehicle-to-vehicle/infrastructure technologies. To guarantee system usability and safety appropriateness, a key precondition is to ensure that driver mental workload and visual demands required for using the system are reasonable. This study explored how drivers’ mental workload and visual demands were affected when driving with an eco-safe driving HMI (human-machine-interface). Four in-vehicle eco-safe HMI information conditions were evaluated, including baseline, advice only, feedback only, and advice & feedback. Two traffic scenarios (stop-sign intersection with traffic vs. stop-sign intersection without traffic) were simulated using an advanced driving simulator. Behavioural variables (e.g. brake force, acceleration), visual variables (e.g. blink metrics, pupil size) and subjective workload scores were collected from 36 licensed Australian drivers. The experiment results showed that the HMI prompted drivers to apply a smooth and stable brake force when they approached the intersection and a smooth acceleration when they left the intersection. Drivers’ mental workload indicated by visual measurements were consistent with their subjective reported workload levels. Drivers had a higher mental workload when they received and processed additional eco-safe information in the advice & feedback condition. An increase in mental workload induced by the in-vehicle cognitive task initiated more blink activities while the increase in visual demand caused by a complex road situation led to blink inhibition. The study shows the HMI could significantly promote eco-safe driving behaivours without causing excessive mental and visual workload of drivers.@en

Mobile phone distracted driving is a recurrent issue in road safety worldwide. Recent research on driving behaviour of distracted drivers suggests that in certain circumstances drivers seem to assume safer behaviours while using a mobile phone. Despite a high volume of research on this topic, self-regulation by mobile phone distracted drivers is not well understood as many driving simulator experiments are designed to impose an equal level of distraction to participants being tested for their driving performance. The aim of this research was to investigate the relationship between self-regulatory secondary task performance and driving. By a driving simulator experiment in which participants were allowed to perform their secondary tasks whenever they feel appropriate, the driving performance of 35 drivers aged 18–29 years was observed under three phone conditions including non-distraction (no phone use), hands-free interactions and visual-manual interactions in the CARRS-Q advanced driving simulator. Drivers’ longitudinal and lateral vehicle control observed across various road traffic conditions were then modelled by Generalized Estimation Equations (GEE) with exchangeable correlation structure accounting for heterogeneity resulting from multiple observations from the same driver. Results show that the extent of engagement in the secondary task influence both longitudinal and lateral control of vehicles. Drivers who engaged in a large number of hands-free interactions are found to select lower driving speed. In contrast, longer visual-manual interactions are found to result in higher driving speed among drivers self-regulating their secondary task. Among the road traffic conditions, drivers distracted by their self-regulated secondary tasks are found to select lower speeds along the s-curve compared to straight and motorway segments. In summary, the applied human-machine system approach suggests that road traffic demands play a vital role in both secondary task management and driving performance.@en