Pedestrian safety is a growing concern for transportation planners and safety engineers, both within North Carolina and across the country. Pedestrians are extremely vulnerable users of the transportation system and can be particularly subject to serious injuries and fatalities in the event of a crash. A proactive approach to address this issue is needed to improve pedestrian safety. Identifying sites with the highest risk of pedestrian-related safety issues across the entire transportation network can then be monitored and/or treated to help improve pedestrian safety. However, this systemic approach to pedestrian safety requires accurate identification and quantification of the risk associated with various site-related features on pedestrian safety performance to be effective. The overall objective of this project is to quantify systemic risk factors for pedestrian safety on North Carolina roads and develop guidance for analysts at NCDOT and local agencies within the state.
Risk factors will be quantified by combining existing datasets, including crash and roadway data from NCDOT, socioeconomic data from the U.S. Census, probe vehicle speed from the Regional Integrated Transportation Information System, land use data, transit ridership data, and others.
Outcomes from this research will include the development of guidance on implementing systemic pedestrian safety analysis in North Carolina, focusing on the identification and use of pedestrian risk factors in both urban and rural areas. Possible applications may include prioritization of corridors for HSIP project studies, input to the NCDOT SPOT scoring model for bicycle and pedestrian projects, or information for highway project scoping reports. The guidance document will include user-friendly diagrams or illustrations for both NCDOT and external stakeholders.
In addition, the project is anticipated to produce a database that incorporates traffic, pedestrian exposure, sociodemographic, transit, and other information that was used to quantify the pedestrian risk factors. The geoprocessing tools and python scripts used to merge GIS databases with NCDOT's LRS will also be provided to facilitate the development of future datasets to support similar research efforts.