Temporal stability of driver injury severity in single-vehicle roadway departure crashes: A random thresholds random parameters hierarchical ordered probit approach

By Miao Yu, Changxi Ma, Jinxing Shen. 2020

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Abstract This study examines contributing variables affecting the driver injury-severity in single-vehicle roadway departure crashes. To capture the threshold heterogeneity and unobserved heterogeneity, the random thresholds random parameters hierarchical ordered probit (HOPIT) approach is employed using the crash data collected from 2014 to 2017 in the State of North Carolina. Three injury severity levels are considered: severe injury, minor injury, and no injury. Attributes that potentially affect crash severity are examined, including driver, crash, roadway, and environmental characteristics. A series of likelihood ratio tests are conducted to examine the temporal stability of factors across different studied years. The marginal effects of factors in different injury-severity models are compared. Significant temporal instability is found among the studied year periods. The threshold value estimated using the random threshold random parameters HOPIT model is found to be random parameters and determined by specific explanatory variables. Additionally, the effects of some factors (e.g., alcohol, curved roadway, passenger car, SUV, and wet/water surface) on injury severity are relatively stable, while others (e.g., female driver, collector, and clear weather) present temporal unstable effects. Regarding the temporal instability, decision-makers need to treat the factors carefully to avoid developing incorrect countermeasures.

Subfields: Public Health, Environmental and Occupational Health, Safety, Risk, Reliability and Quality, Transportation

View Paper: https://www.semanticscholar.org/paper/023e36016857ca1fe4a9448f689de6215d1b7611