Wrong-way driving (WWD) is a dangerous behavior which poses a significant safety risk on limited access facilities. As WWD crashes are rare, it is difficult to build credible statistical models based solely on crashes. Modeling other WWD events, such as citations and 911 calls, can result in more reliable models. Even though these WWD events do not always result in a crash, they can be an effective surrogate for WWD crashes. Analysis of Florida limited access exit ramps found that ramps with multiple WWD crashes from 2011 to 2015 tended to have more WWD citations and 911 calls (WWD entries). Additionally, areas with high WWD crash densities also had high WWD entry densities and 68% of WWD crashes had an associated citation, 911 call, or both. These results show that modeling WWD entries can provide insights into WWD crashes. A model was developed for Florida limited access facilities to identify roadway factors and traffic characteristics of exit ramp terminals that influence WWD entries. This model indicated that interchange type, intersection angle of exit ramp terminals, presence of tolling at the entrance ramp, presence of a channelizing island between the exit ramp lanes, number of lanes on the exit ramp, area (rural or urban), and traffic volumes significantly affect the likelihood of WWD entries at exit ramps. With this model, transportation agencies can better predict WWD entries at exit ramps; identify suitable locations for possible countermeasures; and improve their current design, signing, and pavement marking practices while still following national and state standards.


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    Titel :

    Modeling Wrong-Way Driving Entries at Limited Access Facility Exit Ramps in Florida


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Kayes, Md Imrul (Autor:in) / Sandt, Adrian (Autor:in) / Al-Deek, Haitham (Autor:in) / Uddin, Nizam (Autor:in) / Rogers, John H. (Autor:in) / Carrick, Grady (Autor:in)


    Erscheinungsdatum :

    2019-04-04




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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