Dynamic message signs (DMS) have been widely used by transportation agencies to disseminate traffic information (referred to in this article as “public traffic information”) for decades. Unfortunately, their effectiveness is limited, based on the following reasons: they are costly, can only present a limited amount of information, and typically only display information in one language. The wide availability of smart devices and the development of connected vehicles offer the possibility to create “virtual” DMS (VDMS), utilizing geofencing and audible messages to convey public traffic information. This research compares the ability of VDMS to convey public traffic information with existing DMS. A mixed repeated-measure experiment using a driving simulator was designed that examined the impacts of driver age, information transmission mode, amount of information, and driving complexity on message comprehension. Forty-two participants were recruited and each of them was tested under different combinations of the three within-subject factors. Participant performance was measured in terms of message comprehension, distraction, and self-reported overall difficulty level in receiving messages. Results revealed that VDMS generally performs better than DMS as information content increases and driving condition complexity increases, regardless of driver age. VDMS increased message comprehension by 16% under relatively complex driving conditions, reduced driver reaction time to unexpected stimuli (as measured with a reduced time-to-brake of 0.39 s), and made the same messages easier to process and retain for drivers than DMS. Based on these results, it is recommended that transportation agencies give careful consideration to VDMS as a future strategy for delivering public traffic information in a connected vehicle environment.


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    Title :

    Comparison of In-Vehicle Auditory Public Traffic Information With Roadside Dynamic Message Signs


    Contributors:

    Published in:

    Publication date :

    2016-05-03


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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