Developing a Geospatial Safety Analysis Tool: A Systematic Approach to Identify Safety-Critical Horizontal Curve Segments and Hazardous Contributing Factors
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 7
Abstract
Transportation agencies make substantial efforts to implement safety improvement countermeasures to mitigate safety hazards. However, region-specific safety considerations, rather than accepting more general, widespread methods, and the most ideal investment decisions to improve safety, are often unclear. This is of increased concern for horizontal curve segments, because they are locations of elevated safety risk. Yet, there exists a gap in literature on the development and use of a geospatial tool to investigate horizontal curve safety. To fill this gap, a methodological approach to create a region-specific geospatial horizontal curve safety tool was developed in this research. The tool was created using two regions as application areas to ensure the methodological approach was reproducible and transferable. Geolocated crash data, roadway infrastructure data, and curve data were spatially integrated using a GIS. Bayesian hierarchical models were estimated with crash severity data to gain region-specific safety results. A GIS tool was then derived from the applied model coefficients. The tool was applied to prioritize the most safety-critical horizontal curves and to select optimal countermeasures, especially in cases with specific infrastructure investment identification needs. The results of this research benefit regional agencies in their aim to efficiently distribute investments and identify the most appropriate countermeasures to improve roadway safety in their region.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported in part by the Dwight David Eisenhower Transportation Fellowship Program of the Federal Highway Administration (Grant Agreement No. 93JJ32045003). Some data used during the study were provided by a third party, including all roadway inventory and crash data from Vermont and Maryland. This data can be found as cited in the references Vermont DOT (2016, 2017b, c, 2018a, b, 2019a, b, c) and Maryland DOT (2017, 2019, 2020). Some data, models, and code that support the findings of this study are available from the corresponding author upon reasonable request. The details of the horizontal curvature data can be found at Ai (2021).
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Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 7 • July 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Dec 29, 2021
Accepted: Feb 22, 2023
Published online: Apr 28, 2023
Published in print: Jul 1, 2023
Discussion open until: Sep 28, 2023
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