Citation

Hamilton I, Himes S, Wang Y, Tanzen R, Zhou Y. Transp. Res. Rec. 2023; 2677(2): 431-442.

Copyright

(Copyright © 2023, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981221106788

PMID

unavailable

Abstract

Macro- or planning-level crash prediction models (CPMs) differ from traditional predictive safety models in that they predict crashes for a geographic area rather than at a specific segment or intersection site. These models lend themselves to traditional planning-level activities, particularly when the exact design or dimensions of a road facility have yet to be determined. This paper describes a research effort conducted by the Southern California Association of Governments (SCAG) to develop a series of models to support safety analyses as part of the agency?s quantitative planning approach. The models were found to support SCAG?s planning at two scales: one series of models addressed annual performance measure target setting for the entire SCAG region by predicting severe injuries per year (i.e., annual fatalities, serious injuries, and nonmotorized fatalities and serious injuries), and a second series of models predicted crashes that contribute to agencywide performance measures, but at a community- or neighborhood level. These latter community models predicted crashes at a scale that will assist in evaluating scenarios for future projects or local community growth. The models developed through this research were consistent with previous research and display a promising ability to accurately predict crashes and injuries that are key benchmarks for regional safety planning.

Language: en