Wrong-Way Driving

Abstract

Wrong-way driving (WWD) is one of the most dangerous driver errors or behaviors on limited access facilities. Previous studies focused on analyzing WWD crashes but discovered that WWD crashes were extremely rare. Using WWD 911 calls and WWD citations, which occur much more frequently than WWD crashes, to help predict WWD risk allows roadway agencies to be proactive and implement WWD countermeasures at problem areas instead of waiting for serious WWD crashes to occur. This study developed a model to determine WWD risk according to WWD crashes, citations, and 911 calls. For the development of this novel model, a market basket analysis was used to determine the overlap between the three WWD data sets (crashes, 911 calls, and citations for the years 2011 and 2012 on Florida Interstates and toll roads). The independent WWD events were then used to develop a generalized Poisson regression model that allowed the WWD 911 calls, citations, and crash frequencies to be converted to WWD risk values. WWD risk densities were also calculated by using either vehicle miles traveled or roadway length to consider exposure. The counties and roadways were then ranked with respect to WWD risk values and densities; these rankings indicated that Miami–Dade was a problematic county because it was ranked highest by WWD risk value and its nine Interstates or toll roads were ranked in the top 15 by WWD risk density. The developed model and macroscopic rankings are very useful to help identify counties and roadways where WWD countermeasures should be implemented.