Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34515
Title: Improved traffic safety at work zones through animation-based variable message signs
Authors: Almallah, Mustafa
HUSSAIN, Qinaat 
Alhajyaseen, Wael
PIRDAVANI, Ali 
BRIJS, Kris 
Dias, Charitha
BRIJS, Tom 
Issue Date: 2021
Publisher: Elsevier
Source: Accident analysis and prevention, 159 (Art N° 106284)
Abstract: Work zones are established to provide a safe environment for all road users and road workers. However, based on the statistics, they can be considered as crash prone zones due to changes in the road alignments and the posted speed limits. In this driving simulator study, we aimed at investigating the safety impacts of a newly proposed system composed of graphical and animation-based variable message signs (VMSs) in the state of Qatar. The proposed VMS condition was compared with a control condition that was designed following the Qatar Work Zone Traffic Management Guide. A total of seventy subjects were invited to participate in the experiment voluntarily. Study results showed that in the VMS condition, drivers reduced their traveling speeds in advanced compared to the control condition. Drivers' traveling speed in the VMS condition was significantly reduced by 6.3 and 11.1 km/h on the leftmost and the second leftmost lanes, respectively. Next, the results uncovered that the proposed system motivated drivers to initiate early lane changing maneuvers, i.e., 150 m earlier than the control condition. Finally, the VMS condition was effective in stimulating drivers to keep larger headways with a merging vehicle. In sum, the proposed VMS system outperformed the control condition in terms of speed reduction, early merging, and higher headways between the through and the merging vehicle.
Keywords: Work zones;Lane closure;Variable message signs;Driving simulator;Road safety;Driving behaviour
Document URI: http://hdl.handle.net/1942/34515
ISSN: 0001-4575
e-ISSN: 1879-2057
DOI: 10.1016/j.aap.2021.106284
ISI #: 000686767100002
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

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