3 research outputs found

    Assessing the effects of work zone configurations on drivers\u27 visual attention

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    This study assessed the effects of two different work zone configurations on driver’s visual attention by eye movement monitoring. A driving simulator study was conducted with thirty participants. Variations in traffic density and warning sign placement distance were added to the merge configurations to simulate the real time situation. A 2 x 2 x 3 within-subjects factorial design was used for this research. The independent variables used in this study were (1) merge configuration [(i) Conventional Lane Merge (CLM) and (ii) Joint Lane Merge (JLM)], (2) traffic density [(i) high and (ii) low] and (3) distance between traffic signs [(i) standard distance, (ii) 25% reduction from standard and (iii) 25% increase from standard]. The dependent variable used for this study was the total number of eye movements (gaze) of the participants towards the three mirrors (rear view, left side view and right side view), and towards ‘other areas’ such as dash board, warning signs, environment, and other vehicles etc., were analyzed. Results from the research show that, the total number of gazes at mirrors and ‘other areas’ in CLM and JLM are nearly the same and they are not significantly different (p value: \u3e0.05). Changes in traffic density and sign placement distances have a significant effect on number of gazes at mirrors and ‘other areas’ (p value: \u3c0.05). Gender and driving experience have a significant effect on number of gazes at mirrors, but not at ‘other areas’. Reducing the sign placement distances by 25% from the standard distances does not show any significant effect on the number of gazes at mirrors, however it shows an increase in the number of gazes at ‘other areas’ by nearly 11.6%. An increase in sign placement distances by 25% from the standard distances, show an increase in number of gazes at mirrors by nearly 16.9%, while it does not show any significant effect on the number of gazes at the ‘other areas’

    The Effects of Work Zone Configurations on Physiological and Subjective Workload

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    There is a dearth of research on the effect of driving through work zones on physiological and subjective workload of drivers. The objectives of this research were to (a) study the effect of work zones and traffic density on physiological measures of workload, subjective workload and performance variables (b) study the relationship between physiological measures of workload, subjective workload and performance variables. Conventional lane merge (CLM), joint lane merge (JLM) and a road without a work zone (control) were modeled with high and low traffic density by using a full-size driving simulator. 13 female and 17 male students volunteered to participate in this study. Data regarding physiological measures of workload through heart rate variability measures (RMSSD, LF, HF and LF/HF ratio) were collected by using a heart monitoring watch. NASA-TLX was used to measure subjective workload. Variability in steering, braking and speed were used as performance variables. Results showed that the driving scenarios and traffic density did not affect physiological measures of workload. In terms of subjective workload, CLM and JLM did not differ significantly from each other. However, with respect to mental demand, temporal demand, effort and total workload, CLM was significantly more demanding than the control group. Total workload for driving in high traffic density was 27.2% more than that of in low traffic density. No significant differences were observed in brake variability between different scenarios. However, CLM and JLM had significantly higher speed variability than the control group but they were not significantly different from each other. Steer variability and brake variability were higher in high traffic density. In conclusion, results showed that when it comes to using driving simulators, physiological measures of workload show no sensitivity to changes in the work zone but subjective and performance variables are influenced and can be used to compare different work zone configurations
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