The Role Individual Differences and Environmental Factors in Automated Driving Performance

A series of experiments were conducted to investigate the effects of ADHD diagnosis, inclement weather, non-driving-related tasks (NDRT), automation failures, and traffic density on driving performance and takeover performance. This study also examined the relationship between dispositional factors (i.e., trust in automation, cognitive failures, and self-efficacy) and dynamic factors (i.e., mental workload, situation awareness, and situational trust) in relation to automated driving performance. A total of 156 participants were recruited for this study, including drivers with and without attention-deficit hyperactivity disorder (ADHD). Each participant completed four experimental drives and two baseline drives. Mental workload, heart rate variability (HRV), situational trust, and situation awareness were also measured during the drives. Experiment 1 examined the effects of ADHD diagnosis, inclement weather (rain versus no rain), and non-driving-related tasks (NDRT versus no NDRT) on driving and takeover performance. Results indicated that ADHD drivers exhibited greater steering variability and stronger brake pressure during takeovers in conditions with rain and the NDRT. The presence of both rain and NDRT produced two-way and three-way interactions. The added complexity of rain and the NDRT likely increased the mental workload of non-ADHD and ADHD drivers. For Experiment 2, automation failures were introduced as the environmental manipulation, which involved the absence of a takeover alert in the proximity of an approaching hazard. For Experiment 3, traffic density was introduced in place of NDRTs. Results indicated that high traffic density increased takeover performance and brake pressure. Lastly, following a series of correlation and regression analyses, trust in automation, risk perception, self-efficacy, and cognitive failures were identified as significant predictors of driving performance in all three experiments. Overall, these findings highlight the importance for transportation researchers, traffic engineers, and legislators in prioritizing safety and developing individualized driver profiles when designing HAVs.