Citation

Drawve G, Grubb J, Steinman H, Belongie M. Am. J. Crim. Justice 2019; 44(1): 106-124.

Copyright

(Copyright © 2019, College of Law Enforcement, Eastern Kentucky University, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s12103-018-9449-3

PMID

unavailable

Abstract

Law enforcement's examination of vehicle crashes is often nested in the Data-Driven Approaches to Crime and Traffic Safety (DDACTS) framework which highlights the importance of hot spot analysis. To assist law enforcement efforts, this study explores how two additional spatial techniques, namely risk terrain modeling (RTM) and conjunctive analysis of case configurations (CACC), could be incorporated within the DDACTS framework. RTM was utilized to identify how the built, physical environment contributed to the risk of traffic incidents. RTM identified 6 risk factors related to the occurrence of vehicle crashes, and high-risk places were compared to hot spots on predictive accuracy. CACC was used to explore configurations likely to result in traffic incidents for the priority places. Our findings support the Theory of Risky Places and fit within a vulnerability-exposure framework, providing law enforcement with guidance for identifying places where vehicle crashes are likely to occur in the future. In addition to providing insight for law enforcement, we discuss how law enforcement can develop working partnerships with stakeholders capable of preventing and/or reducing traffic incidents, which is in line with the general DDACTS framework.

Language: en

Keywords

Conjunctive analysis; DDACTS; RTM; Vehicle crashes