alexa Abstract | Identifying Demographical Effects on Speed Patterns in Work Zones Using Smartphone Based Audio Warning Message System

Journal of Ergonomics
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Short Communication Open Access


Objective: The objective of this research is to investigate the impacts of drivers’ demographic factors on speed patterns in response to a smartphone based warning message, while driving through the advance warning area of a work zone.

Methodology: A smartphone application was developed using Massachusetts Institute of Technology (MIT) App Inventor 2, which was used to provide test drivers with a warming message on traffic control and incident awareness. Twenty-four subjects with different demographic features (different gender, age, education background, and driving experience) were recruited to drive through an advance warning area of a work zone twice in two scenarios (with and without the warning message). The advance warning area was divided into three segments for the convenience of analysing the significant difference in subjects’ reactions to the warning messages and the static traffic control signs, in terms of speed patterns.

Findings: Under a traditional traffic control, drivers’ driving speed patterns were not significantly sensitive to the four studied socio-demographic features; but their mean driving speeds and speed variance were noticeable higher than in the situation with an audio warning message. When the smartphone-based messages were provided, drivers drove noticeably slower within the work zone, and the variance became narrower in the most studies of sociodemographic features. Experienced drivers and highly educated drivers drove significantly slower after receiving a warning message from the second and third segment (AWM 2 and 3).

Conclusion: The smartphone-based warning messages were able to help drivers to control their driving speed better for cautious driving in a work zone area, especially for the experienced and highly educated drivers driving through a merging area and an activity area of workers.

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Author(s): Fengxiang Qiao, Ruksana Rahman, Qing Li and Lei Yu


User Experience Design, Ergonomics Softwares

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