2022
DOI: 10.1016/j.jsr.2021.11.011
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An analysis of single-vehicle truck crashes on rural curved segments accounting for unobserved heterogeneity

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Cited by 33 publications
(10 citation statements)
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“…In some cases, the impact of traffic speed on crash severity might not be consistent. In a previous study by Islam et al ( 7 ), for example, medium speed limits between 55 and 65 mph were found to significantly increase the severity of single vehicle-to-truck crashes on curved road sections, while a lower speed limit below 40 mph was likely to decrease the severity. Therefore, instead of using continuous traffic speed data, this study used the real-time 5 min traffic speed data to obtain more specific results.…”
Section: Data Collection and Processingmentioning
confidence: 83%
See 1 more Smart Citation
“…In some cases, the impact of traffic speed on crash severity might not be consistent. In a previous study by Islam et al ( 7 ), for example, medium speed limits between 55 and 65 mph were found to significantly increase the severity of single vehicle-to-truck crashes on curved road sections, while a lower speed limit below 40 mph was likely to decrease the severity. Therefore, instead of using continuous traffic speed data, this study used the real-time 5 min traffic speed data to obtain more specific results.…”
Section: Data Collection and Processingmentioning
confidence: 83%
“…Other previous studies investigated road geometry, weather, or driver-related factors associated with traffic speed and their impacts on crash severity. Islam et al ( 7 ) applied a mixed logit model to identify that a speed limit between 55 and 65 mph is more likely to increase the severity of single vehicle-involved crashes on curved road segments. Kim et al ( 8 ) developed a partial proportional odds model to examine differences in characteristics between types of speeders.…”
Section: Literature Reviewmentioning
confidence: 99%
“…where N is the number of crash observations, and d ik is the indicator variable (1 if individual crash i belongs to crash severity level k, and 0 otherwise). Marginal effects are estimated to determine the effect of a one-unit increase in an explanatory variable (predictor) on severity-outcome probabilities (63). Compared with odds ratios, this method of parameter estimation is simpler to interpret and less affected by the extreme frequency of a particular category belonging to a covariate (64).…”
Section: Multinomial Logit Modelmentioning
confidence: 99%
“…This flexibility leads to improved prediction accuracy, better model fit, and more reliable conclusions 35 . Additionally, Table 1 also showed that there are multiple variants of the random parameters model used for the single-vehicle crash-injury severity in the recent years, including random parameters model that allows for possible heterogeneity in means 9 , 14 , 19 , random thresholds random parameters hierarchical ordered probit model 36 , 37 , correlated random parameters with heterogeneity in means 32 , 38 , and random parameters model that allows both heterogeneity in means and variances 4 , 32 – 34 , 39 , 40 .…”
Section: Literature Reviewmentioning
confidence: 99%