Publications by authors named "Foroogh Hajiseyedjavadi"
Objective: In Bangladesh, drivers' failure to yield to pedestrians at designated crossings poses a significant safety risk and discourages their use of such crossings. The use of behavior change theories could be more appropriate in such complex situations where the interdependent behaviors of drivers and pedestrians interact. While many studies have identified factors that affect drivers' yielding behavior in the literature, fewer efforts have been made to apply behavior change theories in exploring and validating these factors, and to reach a consensus among competing road users.
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- The study explored how users perceive the comfort and naturalness of different automated driving styles using a driving simulator.
- Participants experienced three styles—two mimicking human drivers and one based on a machine learning algorithm—while assessing their preferences on various road conditions.
- Results showed that human-like driving styles were preferred, especially a Defensive approach, while high sensation seekers found the Aggressive style more natural, indicating the importance of psychological factors in user acceptance of automated vehicles.
Previous studies have demonstrated that young drivers fail both to scan for and mitigate latent hazards mostly due to their cluelessness. This study aims to investigate whether these skills could be improved by providing young drivers with alerts in advance of the upcoming threat using a driving simulator experiment. In particular, the warning was presented on the head-up displays (HUD) either 2 s, 3 s or 4 s in advance of a latent threat.
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