Factors Affecting Crash Severity among Elderly Drivers: A Multilevel Ordinal Logistic Regression Approach
نویسندگان
چکیده
This study modeled the crash severity of elderly drivers using data from state Virginia, United States, for period 2014 through to 2021. The impact several exogenous variables on level was investigated. A multilevel ordinal logistic regression model (M-OLR) utilized account spatial heterogeneity across different physical jurisdictions. findings discussed herein indicate that M-OLR can handle and lead a better fit in comparison standard (OLR), as likelihood-ratio statistics comparing OLR models were found be statistically significant, with p-value <0.001. results showed crashes occurring two-way roads are likely more severe than those one-way roads. Moreover, risks older, distracted, and/or drowsy involved escalate undistracted nondrowsy drivers. also confirmed consequences involving unbelted prone belted their passengers. Furthermore, higher-speed or when linked high-speed violations is extreme low-speed operating compliance stated speed limits. Crashes involve animals property damage only, rather result injuries. These provide insights into contributing factors among older Virginia support designs road networks.
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ژورنال
عنوان ژورنال: Sustainability
سال: 2022
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su141811543