01851228

Component

https://doi.org/10.1177/03611981221106788

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.

Ian Hamilton https://orcid.org/0000-0003-0949-5495© National Academy of Sciences: Transportation Research Board 2022.

English

0000-0003-0949-5495

0000-0003-2932-7691

0000-0001-8543-8156

0000-0002-0533-104X

0000-0002-4394-3653

pp 431-442

2023-2

Transportation Research Record: Journal of the Transportation Research Board

Web

References (18)

Crash risk forecasting; Neighborhoods; Transportation planning

Southern California

Highways; Planning and Forecasting; Safety and Human Factors

TRIS, TRB, ATRI

Jul 10 2022 3:00PM