Transportation safety continues to be a serious issue throughout the world. Proven safety measures have been developed to increase the safety on all roadways, but have not been universally and equitably implemented due to lack of resources, inefficiencies, and understanding. Additionally, the relative level of mobility safety remains higher in certain environments than others, creating an inequitable landscape. In this dissertation, the efficiency of using local and statement resources to improve safety is investigated while controlling for level of safety risk in vulnerable environments and locations using a comprehensive approach. Several methodologies and techniques are employed and developed to examine both systematic resource allocation and location-specific resource allocation methods from the perspective of equitably and efficiently using limited funds to increase safety. The approaches in this research include machine learning and regression methods, key informant interviews, employment of surveys, and the development of a geospatial tool. When combined and employed at the regional level, the methods presented in this dissertation can impact regional safety from a myriad of perspectives. The results and conclusions of this research informs transportation policymakers', officials', and researchers' abilities to equitably increase road safety through informed state and regional systematic and site-specific resource allocation processes.