Temporal stability of factors influencing driver-injury severities in single-vehicle crashes: A correlated random parameters with heterogeneity in means and variances approach

Se, Chamroeun; Champahom, Thanapong; Jomnonkwao, Sajjakaj; Karoonsoontawong, Ampol; Ratanavaraha, Vatanavongs

doi:10.1016/j.amar.2021.100179

Cited by 48 publications

(20 citation statements)

References 46 publications

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“…In this regard, the model can be more flexible in uncovering the unobserved heterogeneity by allowing the interaction effect between non-random parameters with the mean and variance of the random parameters on the injury-severity probability. Following the previous studies 32 , 80 , 83 , 84 , 86 , let be a vector of estimable parameters that vary across crash observations, which is derived as: where is a mean parameter estimateed across all crashes 90 , 91 , denotes a vector of the variables that capture heterogeneity in the mean that influences injury severity n, with parameter vector 86 , is a vector of variables that captures heterogeneity in the standard deviation with the corresponding vector 86 , and is a disturbance term.…”

Section: Methodsmentioning

confidence: 85%

“…The following subsections provide a discussion of the results based on the average marginal effect and the coefficient (in the case of random parameters). All parameters presented in the tables have a significance level of 0.1 or lower (indicated by the t-Stat), as this level is considered relatively important to the outcome of injury-severity probabilities 32 .…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies have also reported similar findings 4 , 37 , 98 . As for temporal instability, the reason this variable was not found statistically significant in later periods may be due to the strengthening of law enforcement on drunk driving in Thailand through the Road Traffic Act (2014), which may have influenced driving behavior and drivers' awareness of police checkpoints due to stricter penalties 4 , 32 .…”

Section: Resultsmentioning

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%

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Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Champahom

Wisutwattanasak

et al. 2023

Sci Rep

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Upon detecting a crash impact, the vehicle restraint system locks the driver in place. However, external factors such as speeding, crash mechanisms, roadway attributes, vehicle type, and the surrounding environment typically contribute to the driver being jostled within the vehicle. As a result, it is crucial to model unrestrained and restrained drivers separately to reveal the true impact of the restraint system and other factors on driver injury severities. This paper aims to explore the differences in factors affecting injury severity for seatbelt-restrained and unrestrained drivers involved in speeding-related crashes while accounting for temporal instability in the investigation. Utilizing crash data from Thailand between 2012 and 2017, mixed logit models with heterogeneity in means and variances were employed to account for multi-layered unobserved heterogeneity. For restrained drivers, the risk of fatal or severe crashes was positively associated with factors such as male drivers, alcohol influence, flush/barrier median roadways, sloped roadways, vans, running off the roadway without roadside guardrails, and nighttime on unlit or lit roads. For unrestrained drivers, the likelihood of fatal or severe injuries increased in crashes involving older drivers, alcohol influence, raised or depressed median roadways, four-lane roadways, passenger cars, running off the roadway without roadside guardrails, and crashes occurring in rainy conditions. The out-of-sample prediction simulation results are particularly significant, as they show the maximum safety benefits achievable solely by using a vehicle's seatbelt system. Likelihood ratio test and predictive comparison findings highlight the considerable combined impact of temporal instability and the non-transferability of restrained and unrestrained driver injury severities across the periods studied. This finding also demonstrates a potential reduction in severe and fatal injury rates by simply replicating restrained driver conditions. The findings should be of value to policymakers, decision-makers, and highway engineers when developing potential countermeasures to improve driver safety and reduce the frequency of severe and fatal speeding-related single-vehicle crashes.

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Section: Methodsmentioning

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Champahom

Wisutwattanasak

et al. 2023

Sci Rep

Self Cite

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show abstract

“…The model is estimated using maximum likelihood estimation with logit probabilities. Accounting for the possibility of heterogeneity in the means and variances of random parameters,

represents the parameters that vary across respondents, which are derived by Equation (3) [ 50 , 51 , 52 ]:

where

denotes the mean parameter estimate across all respondents;

represents a vector of explanatory variables capturing heterogeneity in means that influence WTP level i ;

is an estimable parameter vector of

;

is a vector of WTP variables capturing the standard deviation of heterogeneity

, with corresponding vector

, and

is the error term.…”

Section: Methodsmentioning

confidence: 99%

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Wisutwattanasak

Jomnonkwao

et al. 2022

Behavioral Sciences

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Property damage and loss from road traffic accidents are a major concern in developing countries; thus, studies on accident damage in such countries may include more latent factors. This study aims to examine the effect of psychological perspectives and sociodemographic status on drivers’ willingness-to-pay (WTP) for road accident risk reduction, using confirmatory factor analysis (CFA) and the random parameters multinomial logit model with heterogeneity in means and variances (RPMNLHMV). The CFA results from interviews with 1650 car drivers in Thailand demonstrate that concepts of the theory of planned behavior and health access process approach are key factors for describing drivers’ behavioral intention and WTP. The RPMNLHMV results indicate that drivers’ demographics affected drivers’ WTP to reduce road accidents, and psychological perspectives were also found to have an influence on WTP. The results also reveal unobserved characteristics that could affect drivers’ WTP. The study concludes that ignoring unobserved heterogeneity in studies on WTP to reduce road accidents can lead to biased results and neglect important influential factors. The methodological approaches applied herein offer another layer of insight into unobserved characteristics in road accident valuation. These findings could be used to provide relevant authorities practical insights for policy development on road accident mitigation and road safety education programs in accordance with drivers’ characteristics.

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Temporal analysis of cellphone-use-involved crash injury severities: Calling for preventing cellphone-use-involved distracted driving

Song

Meng

2022

Accident Analysis & Prevention

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Temporal stability of factors influencing driver-injury severities in single-vehicle crashes: A correlated random parameters with heterogeneity in means and variances approach

Cited by 48 publications

References 46 publications

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Temporal instability and differences in injury severity between restrained and unrestrained drivers in speeding-related crashes

Influence of Psychological Perspectives and Demographics on Drivers’ Valuation of Road Accidents: A Combination of Confirmatory Factor Analysis and Preference Heterogeneity Model

Temporal analysis of cellphone-use-involved crash injury severities: Calling for preventing cellphone-use-involved distracted driving

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