• Developing a Data-Driven Safety Assessment Framework for RITI Communities in Washington State

      Wang, Yinhai; Sun, Wei; Yang, Hao; Gottsacker, Christopher; Ricord, Sam; Yin, Shuyi (2019-10-03)
      In the history of this country, rural, isolated, indigenous, and tribal (RITI) communities were commonly overlooked with regards to social infrastructure and support. This issue is evident in the development of the transportation networks of these areas and the distinct lack of road safety in these types of communities. RITI communities carry a significantly disproportionate amount of traffic collisions and fatalities compared to urban areas. In order to improve the traffic safety conditions of the RITI communities in Washington State, it is necessary to build a traffic safety management system. A baseline data platform was developed by integrating the collected safety related data for the RITI communities in Washington State in the Year 1 Center for Safety Equity in Transportation (CSET) project. Besides the baseline data, the traffic safety management also requires the safety assessment framework, which is the corner stone of the traffic safety management system. Therefore, this project aims to develop a data-driven safety assessment framework to enable an effective roadway safety management system and improve the traffic safety conditions for RITI communities. The framework is based on an effective and efficient database management system for traffic and crash-related data of the RITI communities. In addition, in order to assist transportation agencies in practices such as the identification of high-risk roadway segments, the developed database management system has powerful visualization functions. Besides the database management and visualization platform, this project also develops roadway safety performance indices and traffic safety assessment methods in the safety assessment framework. This project also provides guidance on how to utilize these safety performance indices and results of safety assessment methods for visualization and analysis.