A correlated random parameters tobit model to analyze the safety effects and temporal instability of factors affecting crash rates

Hou, Qinzhong; Huo, Xiaoyan; Leng, Jinsong

doi:10.1016/j.aap.2019.105326

Cited by 47 publications

(16 citation statements)

References 48 publications

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“…Studies also show that setting more gradual horizontal curves can reduce the number of accidents [46]. The deflection angle found positively correlated with the probability of accidents and left turn curves were observed to be more dangerous than right turn curves leading to different design of safety measures [37,52]. The length of horizontal curve was found negatively associate with the likelihood of accident occurrence [37].…”

Section: Geometric Design Elementsmentioning

confidence: 88%

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Accident prediction modelling for expressways: a review

Kumar

Jain

Singh

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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Expressways are the need for fast movement of goods and human being for long distances in current scenario for every country, but at the same time these facilities have the highest severity rate among all the road categories. Various researchers around the world have tried to find out the effect of traffic volume, road geometry and environmental factors on frequency of accident on expressway by using different accident prediction modeling methods during last three decades. The purpose of this review paper is to find out the appropriate modeling method which can be used to predict accident frequency on the expressways in the developing country like India where traffic conditions, vehicular characteristics, and the driver behaviour are very different from the developing countries and to find out the research areas where the findings are inconclusive. Literature review suggests that among various models used so far, correlated random parameter model found to be the most advanced model to simultaneously account for both the heterogeneous effects of explanatory factors across the road segments and the cross correlations among the random parameter estimates. Findings related to variables like percentage of heavy vehicles, vertical gradient and lane width are not conclusive. However, safety effect of variables like speed limit, roadway lighting, pavement type and fog are less studied on expressway. The effect of allowing two wheelers on the expressways safety has not been studied yet, and the accidents related to fatigue or drowsiness also need examination.

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Section: Geometric Design Elementsmentioning

confidence: 88%

“…Both inside and outside shoulder widening were found associated with decreased accident count [30,44,46,51,52].…”

Section: Cross-section Elementsmentioning

confidence: 97%

Accident prediction modelling for expressways: a review

Kumar

Jain

Singh

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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“…For the CRPNBHM model, the standard deviations of the mixing distributions for correlated random parameters can be computed as the square roots of the diagonal elements of the variance-covariance matrix Σ For the statistical significance of these standard deviations, the z-stat can be computed according to the software-generated observation-specific estimates of the standard deviations corresponding to the correlated random parameters by ( 14, 15, 17, 19 ):…”

Section: Methodsmentioning

confidence: 99%

“…Recent studies have shown that ignoring the underlying interactions may result in biased estimations and restrictive inferences (8,13). Over the last few years, the interactions of unobserved characteristics have been increasingly studied by introducing correlations between random parameters into the model (14)(15)(16)(17)(18)(19). In addition, a few studies have investigated the unobserved heterogeneity resulting from the interactions of observed factors by allowing the means/ variances of random parameters to be an estimable function of explanatory variables (20)(21)(22)(23)(24)(25).…”

mentioning

confidence: 99%

A Correlated Random Parameters Model with Heterogeneity in Means to Account for Unobserved Heterogeneity in Crash Frequency Analysis

Huo

Leng

Hou

et al. 2020

Transportation Research Record

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Unobserved heterogeneity induced by omitted variables is a major challenge in developing reliable road safety models. In recent years, the random parameters negative binomial (RPNB) model has been used frequently in crash frequency analysis to account for unobserved heterogeneity. However, the majority of past studies of the RPNB model assumed that there was no correlation between different sources of unobserved heterogeneity, which is not always true given the complex interactions of safety factors. Compared with the RPNB model, a more flexible random parameters model that is the correlated random parameters negative binomial with heterogeneity in means (CRPNBHM) model was proposed in this study. Results indicate that the CRPNBHM model could not only capture the otherwise unobserved heterogeneity, but also track the underlying correlation among different sources of unobserved heterogeneity, thus outperforming the RPNB model. In addition, new insights into the interactions of safety factors (e.g., the joint safety effects of heavy trucks and pavement rutting depth) were obtained from the CRPNBHM model and these are expected to be beneficial in developing effective safety countermeasures. Results from this study demonstrated the CRPNBHM model to be a good alternative for crash frequency analysis, particularly when unobserved heterogeneity was detected.

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“…This approach may be warranted as opposed to incorporating spatial and temporal effects depending on the models' goodness of fits. The URPOPIE model may be applied to gain more profound insights on the temporal instabilities of the crash contributing factors as well (37). When it comes to sample size requirements, random parameters models, in general, require large samples (38).…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

Two-Lane Highway Crash Severities: Correlated Random Parameters Modeling Versus Incorporating Interaction Effects

Farid

Alrejjal

Ksaibati

2021

Transportation Research Record

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Two-lane highways represent the majority of highways in the U.S. and their safety is of crucial concern. Even though road safety researchers intensively evaluated two-lane highway safety, past studies were challenged by a methodological hindrance, namely that of correlated random parameters (CRP) modeling methods. Random parameters models capture unobserved heterogeneity effects of crash contributing factors, while CRP models offer the additional benefit of capturing correlations among variables inducing such unobserved heterogeneity effects. However, CRP models do not permit specifying pairs of regressors, with statistically insignificant correlations, to be uncorrelated. In this research, it was demonstrated that the conventional uncorrelated random parameters ordinal probit (URPOP) structure with interaction effects outperformed the correlated random parameters ordinal probit (CRPOP) structure when modeling injury severity risks of two-lane highway crashes in Wyoming. As per the former model’s results, speeding, head-on collisions, sideswipe opposite-direction collisions, intersecting-direction collisions, motorcycle involvement, impaired driving, distracted driving, the interaction effect of speeding with motorcycle involvement, that of head-on collisions with impaired driving, and that of head-on collisions with commercial vehicle involvement all raised the likelihood of sustaining severe injuries. Conversely, leaving the crash scene, proper seat belt use, wet road surfaces, and the interaction effect of impaired driving with motorcycle involvement alleviated the risk of incurring severe injuries. The superiority of the proposed model and its reduced computation time warrant its recommendation for implementation in future studies. Also, from a practical perspective, safety mitigation measures are suggested based on this research’s findings.

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A correlated random parameters tobit model to analyze the safety effects and temporal instability of factors affecting crash rates

Cited by 47 publications

References 48 publications

Accident prediction modelling for expressways: a review

Accident prediction modelling for expressways: a review

A Correlated Random Parameters Model with Heterogeneity in Means to Account for Unobserved Heterogeneity in Crash Frequency Analysis

Two-Lane Highway Crash Severities: Correlated Random Parameters Modeling Versus Incorporating Interaction Effects

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