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Identifying community-level disparities in access to driver education and training: Toward a definition of driver
Megan Ryerson1, Joshua Davidson2, Jasmine Siyu Wu2
1Department of City and Regional Planning and Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
Objective:
Obtaining a license may be challenging for teens due to access to driving instruction; in some states, behind-the-wheel (BTW) instruction is required to secure a license before age 18. We investigate spatial accessibility to BTW centers, and how this geographic distribution intersects with metrics of social disparity at the metropolitan level, toward identifying Driver Training Deserts (DTDs): geographic areas of disconnection to driver training.
Methods:
For the Columbus OH region, we collect socioeconomic variables at the Census tract unit of analysis and geocoded locations of public and private BTW training centers and estimate travel time to the nearest BTW training center. We define travel time as either the mean or the maximum travel time to BTW centers across all 1 km × 1 km grid cells within a Census tract. We employ spatial statistical approaches, including homogeneous/inhomogeneous K functions, to determine whether BTW training centers are clustered. Next, we define DTDs as Census tracts with a poverty rate and travel time to BTW centers larger than the 75th percentile values across the region.
Results:
BTW training centers are spatially clustered across the region; the magnitude of this clustering is so great that BTW centers exhibit statistically significant patterns of clustering, even when considering the underlying spatial distribution of socio-economic characteristics. We find that 11-27 Census tracts are identified as DTDs depending on the definition of travel time. DTDs contain a disproportionate percent of the high poverty population (8.7-23.5%) and, depending on the definition of travel time, a disproportionately large African American population.
Conclusions:
Methodologically, defining DTDs necessitates a fine-grained spatial approach as suburban and rural Census tracts tend to be large and thus can be poorly represented by travel times averaged over the Census tract. Defining DTDs as a measure of individual-specific variables - income and impedance - allows DTDs to be addressed with policy interventions. The findings motivate future research correlating DTDs with licensure rates, enrollment in driver training, and safe driving outcomes to understand if DTDs can help explain health equity outcomes related to young driver safety.
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