Comparison of Driver Behavior by Time of Day and Wet Pavement Conditions

Authors

    Authors

    V. V. Dixit; V. V. Gayah;E. Radwan

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    J. Transp. Eng.-ASCE

    Keywords

    Two-fluid model; Driver aggressiveness; Urban traffic networks; Wet; pavement; Time of day; ARTERIAL STREETS; 2-FLUID MODEL; QUALITY; Engineering, Civil; Transportation Science & Technology

    Abstract

    This study uses the two-fluid model for traffic flow, to examine driver behavior during both wet and dry pavement conditions and various times of the day. It was found that parameters in the two-fluid model known to be strongly affected by driver behavior (particularly driver aggressiveness) were statistically different between wet pavement and dry pavement conditions. The results confirmed that drivers tend to behave more conservatively when the pavement was wet compared with dry. The parameters of the two-fluid model were found to be statistically different for the morning peak period from the midday and evening peak periods, the results of which indicated that drivers behave more aggressively during the morning peak. Although these findings have been observed in previous studies, they have not been quantified using traffic data. This study shows that the two-fluid model apart from being a measure of network performance may be able to unveil more about driver behavior. There is a strong possibility that the parameters of the model may be used by researchers as a surrogate measure of safety and could lead to a measure to evaluate aggressive driving. DOI: 10.1061/(ASCE)TE.1943-5436.0000400. (C) 2012 American Society of Civil Engineers.

    Journal Title

    Journal of Transportation Engineering-Asce

    Volume

    138

    Issue/Number

    8

    Publication Date

    1-1-2012

    Document Type

    Article

    Language

    English

    First Page

    1023

    Last Page

    1029

    WOS Identifier

    WOS:000312767000007

    ISSN

    0733-947X

    Share

    COinS