Methodological Approach to Spatiotemporal Optimization of Rural Freeway Enforcement in Florida. Issue 1 (January 2014) - Carrick, Grady; Bejleri, Ilir; Ouyang, Yiqiang
For years, scientists and safety advocates have used various statistical methods to understand when, where, and why traffic crashes happen. Improved traffic crash data systems, including the geographic information system (GIS), are helping to identify when, where, and why traffic crashes occur. Because the vast majority of motor vehicle traffic crashes are attributed to some type of driver error, the need for traffic law enforcement is evident. Traffic law enforcement holds the promise of being an effective part of regulating and modifying the behavior of drivers, and, therefore, it is part of an effective countermeasure strategy. GIS and other methods have been used to identify problem locations or hot spots, but networkwide crashes and enforcement have not traditionally been considered. If a general deterrent effect is derived from visible traffic law enforcement, then when and where the countermeasure is applied become prominent. This research used GIS to spatially relate nearly 10, 000 crashes and more than 179, 000 citations issued on approximately 800 mi of rural freeways in Florida. Traffic volume data were used to normalize the data set and were analyzed with descriptive statistics and enforcement-to-crashes ratios. When historical crash data and historical enforcement data were related, significant spatial and temporal misalignment was apparent. Opportunities to optimize the time and place of traffic enforcement were identified through this analysis.