Abstract
Limited road safety based spatial analysis studies have been conducted in developing countries. Also, little is known about the relationships between province-level road safety performance indexes (RSPIs). Hence, spatial, regression and correlation analysis were used to identify road safety-deficient provinces and determine the relationship between RSPIs. The gathered data comprise 14 RSPIs and nine socioeconomic indicators. Moran’s I and Local Moran indexes were used for conducting the spatial analysis. The natural breaks method was used to cluster similar provinces according to RSPIs. Regarding studied RSPIs, huge local clusters of provinces detected. Eastern provinces had higher road traffic crash (RTC) severity indexes. RTCs were more severe in regions with lower income level. Regions with higher socioeconomic indexes such as population had higher RTC rates. Using RSPIs calculated with distinct exposure measures creates completely different local cluster maps. significant relationships between studied RSPIs were detected. A standard system is needed to organize and categorize the RSPIs. Road safety policies should be region-specific to reduce RSPIs efficiently. Regarding the observed various locations of hot spots in terms of studied RSPIs, further consideration should be given in the process of selecting an RSPI for comparing administrative divisions of a country.
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