Examination of the severity of two-lane highway traffic barrier crashes using the mixed logit model

2020

Algorithms

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Road departure crashes tend to be hazardous, especially in rural areas like Wyoming. Traffic barriers could be installed to mitigate the severity of those crashes. However, the severity of traffic barriers crashes still persists. Besides various drivers and environmental characteristics, the roadways and barrier geometric characteristics play a critical role in the severity of barrier crashes. The Wyoming department of transportation (WYDOT) has initiated a project to identify and optimize the heights of those barriers that are below the design standard, while prioritizing them based on the monetary benefit. This is to optimize first barriers that need an immediate attention, considering the limited budget, and then all other barriers being under design. In order to account for both aspects of frequency and severity of crashes, equivalent property damage only (EPDO) was considered. The data of this type besides having an over-dispersion, exhibits excess amounts of zeroes. Thus, a two-component model was employed to provide a flexible way of addressing this problem. Beside this technique, one-component hierarchical modeling approach was considered for a comparison purpose. This paper presents an empirical cost-benefit analysis based on Bayesian hierarchical machine learning techniques. After identifying the best model in terms of the performance, deviance information criterion (DIC), the results were converted into an equation, and the equation was used for a purpose of machine learning technique. An automated method generated cost based on barriers’ current conditions, and then based on optimized barrier heights. The empirical analysis showed that cost-sensitive modeling and machine learning technique deployment could be used as an effective way for cost-benefit analysis. That could be achieved through measuring the associated costs of barriers’ enhancements, added benefits over years and consequently, barrier prioritization due to lack of available budget. A comprehensive discussion across the two-component models, zero-inflated and hurdle, is included in the manuscript.

mentioning

confidence: 99%

Two-Component Bayesian Hierarchical Models for Cost-Benefit Analysis of Traffic Barrier Crash Count

2020

Algorithms

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“…It has been highlighted in the literature that the impact of barrier height should not be separated from the impact of shoulder width, but rather considered as an interaction term impacting the barrier crash severity. 22 This is especially important as barrier height is the only factors that would be changed in the optimization process and not accounting for an interaction term would result in a biased and erroneous results. That is despite the fact that there are some uncertainties in the interaction terms of shoulder width and barrier heights (p-value > 0.05).…”

Section: Ta B L Ementioning

confidence: 99%

Cost–benefit analysis of traffic barrier geometric optimization, a hurdle machine learning‐based technique

2021

Engineering Reports

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Although it is well documented that optimized barrier dimensions would yield a benefit by enhancement of traffic safety, not many studies have been conducted quantifying how much money could be saved by enhancing barriers to their optimum heights, especially with the help of machine learning technique. Equivalent property damage only (EPDO) was considered as a response in the modeling to account for both aspects of crash frequency and severity. A hurdle model was developed to explore the impact of enhancing the geometric characteristics of barriers while accounting for zero inflation. The two components of the model, logistic regression and truncated negative binomial, could account for both abundance of zeroes and the skewed nature of non-zero EPDO. The methodological approach provides a new understanding of the economic/monetary evaluation of an asset enhancement in the state with the help of machine learning technique. Our methodological approach provides the policy makers about the monetary benefit that they could expect by optimization of barriers heights. The analysis summarized in this paper will not only help Wyoming, but it provides other states with the justification of safety enhancement to their road barriers or assets.

“…The effects of various geometric characteristics of median barriers were evaluated using the random-parameter model [4]. The results indicated that concrete barriers are more prone to the severity of barriers' crashes.…”

Section: Traffic Barriers and Shoulder Widthmentioning

confidence: 99%

Trivariate Copula for Modeling Barriers Crash Severity, Accounting for Policy Endogeneity

2021

Future Transportation

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Studies have been implemented in the literature to enhance the safety of traffic barriers by identification of the contributory factors to those crashes. However, almost all those past studies are subject to potential pitfalls of just answering the cause-and-effect question by traditional statistical methods, which fail to account for possible endogeneity. Modeling traffic barrier crash severity with traditional statistical methods might be biased as many parameters such as barrier’s types is endogenous to unseen factors including policy makers’ decisions in allocating those barriers. Not accounting for the possible endogeneity in the dataset and ignoring correlation between regressors’ error terms might result in biased or erroneous coefficients’ estimates. That is especially true in the presence of strong correlations across models’ error terms. Thus, this study was conducted to model barriers’ crash severity by taking into consideration the endogeneity and correlations across the models’ error terms. Here, the trivariate copula-based method was implemented to simultaneously model traffic barrier crash severity, shoulder width and barrier’s types, while accounting for interrelationships across the models’ error terms. The results provide strong evidence of correlations between the unseen factors to the selections of barrier’s types, shoulder width installation, and crash injury levels. For instance, we found in the presence of accounting for endogeneity and correlation between unseen factors, concrete traffic barrier type and higher shoulder width installation are negatively correlated with unseen factors contributing to severe barriers’ crashes That is despite the fact that the observed factors of those predictors were found to have a reverse impact on the severity of barriers’ crashes.