Development of Decision Support Tools to Assess Pedestrian and Bicycle Safety: Focus on Population, Demographic and Socio-economic Spectra
- PIs: Chimba, Triplett – Tennessee State University
- Project Period: July 1, 2014 – June 30, 2016 (24 months)
With continuous fluctuation of fuel prices and economic uncertainties, many communities are seeing large increases in bicycling and walking as an alternative mode of transportation. Though they are becoming increasingly popular, the users of these two modes of transportation are vulnerable and often associated with severe injury traffic crashes. Most of these severe injuries are avoidable; as such it is very important to address bicycle and pedestrian safety as part of improving community livability. Vulnerability comes from the fact that most collisions between pedestrians or bicycles and vehicles result in severe injury or fatality. One way to address this vulnerability is to develop a framework of identifying possible hotspots for pedestrian and bike related crashes. It is not uncommon to find different pedestrian and bicycle crash preventive programs initiated by agencies such as cities, MPOs, counties and even states failing to produce desired outcomes because of the lack of reliable methodologies to forecast crash hot spots. The problem in most cases comes from the failure to identify which roadway locations, demographic or traffic characteristics are prone to pedestrian and bicycle crashes. To be proactive on improving the safety of pedestrians and bicyclists, it is important to develop methodologies which can be used to identify the presence of hazardous locations for pedestrian and bicyclist collisions. This is because sometimes the challenge comes on where in terms on actual roadway segments, corridors, intersections, or neighborhood should be focused and funds be allocated to improve safety countermeasures effective for reducing bicycle and pedestrian crashes. This research will therefore develop a framework to identify bicycle and pedestrian high crash locations for safety improvement prioritization focusing on Population, Demographic and Socioeconomic Spectra with the state of Tennessee as a case study. Research approach will therefore comprise in-depth analysis using a combination of existing data, data collection in the field, literature review, questionnaire surveying (if applicable), GIS, cluster analysis, and advanced statistical modeling to examine and identify bicycle and pedestrian high crash locations. Relevant data from each of the selected study locations will be integrated into a Geographic Information System (GIS). The data will include crashes, roadway geometry, population, demographics and economic, and traffic. The study will use the gathered data and information to develop safety performance functions (SPF) to identify magnitude and characteristics of variables associated with pedestrian and bicycle safety hazardous locations (black spots). From the SPF, the research will develop criterion for identification of bicycle and pedestrian high crash locations and framework to prioritize funding of bicycle and pedestrian improvements to improve safety. The methodologies developed will be transferable for use in other states utilizing variables and factors commonly associated with pedestrian and bicycle safety throughout the US.