Nonlinear effects of traffic statuses and road geometries on highway traffic accident severity: A machine learning approach.

ABSTRACT: The purpose of this study is to explore nonlinear and threshold effects of traffic statuses and road geometries, as well as their interactions, on traffic accident severity. In contrast to earlier research that primarily defined road alignment qualitatively as straight or curved, flat or slope, this study focused on the design elements of road geometry at accident locations. Additionally, this study considers the traffic conditions on the day of the accident, rather than the average annual traffic data as previous studies have done. To achieve this, we collected road design documents, traffic-related data, and 2023 accident data from the Suining section of the G42 Expressway in China. Using this dataset, we tested the classification performance of four machine learning models, including eX

SUBMITTER: Liang Y 

PROVIDER: S-EPMC11584126 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature