Spatial investigation of aging-involved crashes: A GIS-based case study in Northwest Florida

• Published in: Journal of transport geography 2017-01, Vol.58, p.71-91
• Main Authors: Ulak, Mehmet Baran, Ozguven, Eren Erman, Spainhour, Lisa, Vanli, Omer Arda
• Format: Article
• Language: English
• Subjects: Age; Aging; Aging populations; Case studies; Crash analysis; Crashes; Data processing; Density ratio; Geographic information systems; Government agencies; Maxima; Regression analysis; Remote sensing; Satellite navigation systems; Spatial analysis; Spatial density analysis; Spatial dependence; Statistical analysis; Traffic accidents & safety; Traffic information; Traffic models; Traffic safety
• ISSN: 0966-6923; 1873-1236
• DOI: 10.1016/j.jtrangeo.2016.11.011

This study attempts to understand the unique nature of crashes involving aging drivers, unlike many previous crash-focused traffic safety studies mostly focusing on the general population. The utmost importance is given to answering the following question: How do the crashes involving aging drivers vary compared to crashes involving other age groups? To achieve this objective, a three-step spatial analysis was conducted using geographic information systems (GIS) with a case study application on three urban counties in the Northwest Florida region, based on crash data obtained from the Florida Department of Transportation (FDOT). First, crash clusters were investigated using a kernel density estimation (KDE) approach. Second, a crash density ratio difference (DRD) measure was proposed for comparing maxima-normalized crash densities for two different age groups. Third, a population factor (PF) was developed in order to investigate effect of spatial dependency by incorporating the effect of both number and percent of 65+ populations in a region. This spatial analysis was followed by a logistic regression-based approach in order to identify the statistically significant factors that can help investigate the distinct patterns of crashes involving aging drivers. Results of this study indicate that crashes involving aging drivers differ from other age group crashes both spatially and temporally. Further, the DRD and PF factors are useful metrics to identify and investigate important regions of study. The GIS-based knowledge gained from this research can contribute to the development of more reliable aging-focused safety plans and models. •Aging-involved crashes differ from other crashes both spatially and temporally.•Aging-involved crash density maps have a unique geo-spatial pattern.•Spatial distributions of aging adults and aging-involved crashes are strongly correlated.•Key factors that influence the likelihood of aging-involved crashes are identified.