4.6 Article

A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity

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ELSEVIER
DOI: 10.1016/j.amar.2022.100215

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Snowy weather; Traffic safety; Hazard-based duration model; Random parameters; Heterogeneity in means; Heterogeneity in variances; Temporal instability

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This paper introduces a novel measure for evaluating motor vehicle safety during snowfalls by measuring the time between the start of a snowfall and the occurrence of a motor vehicle accident. The authors use detailed accident information from 2017 to 2020 in New York to explore the impact of different factors on this time period. The findings reveal several factors that affect the timing of accidents during snowfalls.
The present paper introduces the time between the start of a snowfall and the occurrence of a motor vehicle accident as a novel measure for evaluating motor vehicle safety during snowfalls. Detailed information of accidents that occurred during snowfalls between 2017 and 2020 in the state of New York are used to explore the accelerating or delaying effect of different factors on the time between the start of a snowfall and the occurrence of an accident. To that end, the hazard-based duration modeling framework is employed, and to account for multiple layers of unobserved heterogeneity, a random parameters with heterogeneity in means and variances approach is introduced - for this first time, to the authors' knowledge. The temporal stability of the factors across the study period is investigated through conducting a series of systematic likelihood ratio tests, and the factors are not found to be temporally stable across the study years. Hence, separate year-specific models are estimated. The results show that a number of factors affect the time between the start of a snowfall and the occurrence of a motor vehicle accident such as: visibility conditions; concrete road sections; road sections with high Pavement Condition Index (PCI); roads with more than 4 lanes in both directions; locations in close proximity to bus stations; the period during the cold winter months (specifically February); the amount of accumulated snow on the ground before snowfall; the presence of ramps; and long time intervals between snowfalls (especially for heavy snow conditions and adverse visibility conditions). The findings from this paper are anticipated to offer insights to winter maintenance teams, transportation system operators, and users regarding accident-prone periods and locations during snowfalls.(c) 2022 Elsevier Ltd. All rights reserved.

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