Elena Orlova
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Elena Orlova has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Anshu Bamney
School of Civil and Environmental Engineering, Indian Institute of Technology (IIT) Mandi, Mandi 175075, Himachal Pradesh, India
1 shared publication - Eric Jackson
University of Connecticut, the United States of America
1 shared publication - Kai Wang
Connecticut Transportation Institute, University of Connecticut, Storrs, CT
1 shared publication - Manmohan Joshi
Connecticut Transportation Safety Research Center, Connecticut Transportation Institute, University of Connecticut, Storrs, CT 06269, USA
1 shared publication - Niloufar Shirani-Bidabadi
Connecticut Transportation Safety Research Center, Connecticut Transportation Institute, University of Connecticut, Storrs, CT 06269, USA
1 shared publication - Paul Young Joun Ha
Connecticut Transportation Safety Research Center, Connecticut Transportation Institute, University of Connecticut, Storrs, CT 06269, USA
1 shared publication
Latest Publications
- Open Access
Evaluating the Influence of Alert Modalities on Driver Attention Transitions Under Visual Distraction: A Sequence Analysis Approach
This study evaluates how different alert conditions influence driver attention transitions under conditions of visual distraction using sequence analysis. Employing a within-subject experimental design, 13 participants underwent trials in a driving simulator, experiencing three distinct alert conditions: face-tracking auditory alerts, steering wheel auditory torque alerts, and a control scenario without alerts. An eye-tracking system was used to capture drivers’ gaze durations and sequences across three key areas of interest: road, dashboard, and tablet-based infotainment system. Analysis involved computation of transition probabilities, Markov chain modeling for long-term attentional distributions, and entropy analyses to quantify the randomness of gaze transitions. Results showed that face-tracking alerts significantly increased the likelihood of gaze redirection to the road compared to the other conditions, enhancing both immediate and sustained attention. Steering wheel torque alerts demonstrated minimal effectiveness, sometimes performing worse than the no-alert condition due to their passive nature, allowing drivers to bypass attention redirection. Steady-state analyses confirmed that face alerts notably improved sustained driver focus on the road by approximately 3.6%, reinforcing their utility for prolonged attentional control. Entropy analyses further revealed that face alerts provided an optimal balance between structured attention shifts and behavioral flexibility, enhancing attentional predictability. Findings are consistent with previous literature, emphasizing the superior effectiveness of active, gaze-based interventions over passive mechanisms. This research underscores the importance of designing proactive alert systems in vehicle safety technology to effectively mitigate visual distraction-related risks.
Open AccessEvaluating the Influence of Alert Modalities on Driver Attention Transitions Under Visual Distraction: A Sequence Analysis Approach
This study evaluates how different alert conditions influence driver attention transitions under conditions of visual distraction using sequence analysis. Employing a within-subject experimental design, 13 participants underwent trials in a driving simulator, experiencing three distinct alert conditions: face-tracking auditory alerts, steering wheel auditory torque alerts, and a control scenario without alerts. An eye-tracking system was used to capture drivers’ gaze durations and sequences across three key areas of interest: road, dashboard, and tablet-based infotainment system. Analysis involved computation of transition probabilities, Markov chain modeling for long-term attentional distributions, and entropy analyses to quantify the randomness of gaze transitions. Results showed that face-tracking alerts significantly increased the likelihood of gaze redirection to the road compared to the other conditions, enhancing both immediate and sustained attention. Steering wheel torque alerts demonstrated minimal effectiveness, sometimes performing worse than the no-alert condition due to their passive nature, allowing drivers to bypass attention redirection. Steady-state analyses confirmed that face alerts notably improved sustained driver focus on the road by approximately 3.6%, reinforcing their utility for prolonged attentional control. Entropy analyses further revealed that face alerts provided an optimal balance between structured attention shifts and behavioral flexibility, enhancing attentional predictability. Findings are consistent with previous literature, emphasizing the superior effectiveness of active, gaze-based interventions over passive mechanisms. This research underscores the importance of designing proactive alert systems in vehicle safety technology to effectively mitigate visual distraction-related risks.