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

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 179
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Machine Learning ◽  
Cost Benefit Analysis ◽  
Critical Role ◽  
Cost Benefit ◽  
Benefit Analysis ◽  
Machine Learning Technique ◽  
Bayesian Hierarchical ◽  
Automated Method ◽  
Two Component ◽  
Learning Technique

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.

Life Quality Index–based cost–benefit analysis of equipping life preservers aboard airplanes

2021 ◽  
pp. 095441002199329
Author(s):  
Rui-liang Yang ◽  
Li-bin Yang ◽  
Li-jing Wang ◽  
Sha Li ◽  
Dong-han Geng
Keyword(s):  
At Risk ◽  
Quality Index ◽  
Cost Benefit Analysis ◽  
Critical Role ◽  
Life Quality ◽  
Cost Benefit ◽  
Flight Path ◽  
Benefit Analysis ◽  
Occupant Safety ◽  
Life Quality Index

The life preservers aboard airplanes play a critical role in ensuring occupant safety in water-related accidents. However, several airlines off-load life preservers to save fuel and costs. In this study, a cost–benefit analysis was performed considering the Life Quality Index to examine the necessity of life preservers aboard aircraft. It was noted that the placement of life preservers aboard airplanes was reasonable and beneficial in the recent 15 years. Although life preservers are primarily required for extended overwater (EOW) operations, the distance from the shoreline for most of the water-related accidents was considerably smaller than that of an EOW operation, and most water-related accidents occurred close to an airport. In other words, air passengers were at risk of water-related accidents, regardless of whether the flight was classified as an EOW flight. Thus, life preservers must be made available for all the occupants on all passenger flights, regardless of the flight path.

scholarly journals Application of Bayesian Hierarchical Negative Binomial Finite Mixture Model for Cost-Benefit Analysis of Barriers Optimization, Accounting for Severe Heterogeneity

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 288
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Mixture Model ◽  
Negative Binomial ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Finite Mixture Model ◽  
Finite Mixture ◽  
Optimum Number ◽  
Benefit Analysis ◽  
Bayesian Hierarchical ◽  
Highway System

The Wyoming Department of Transportation (WYDOT) initiated a project to optimize the heights of barriers that are not satisfying the barrier design criteria, while prioritizing them based on an ability to achieve higher monetary benefits. The equivalent property damage only (EPDO) was used in this study to account for both aspects of crash frequency and severity. Data of this type are known to have overdispersion, that is having a variance greater than the mean. Thus, a negative binomial model was implemented to address the over-dispersion issue of the dataset. Another challenge of the dataset used in this study was the heterogeneity of the dataset. The data heterogeneity resulted from various factors such as data being aggregated across two highway systems, and the presence of two barrier types in the whole state. Thus, it is not practical to assign a subjective hierarchy such as a highway system or barrier types to address the issue of severe heterogeneity in the dataset. Under these conditions, a finite mixture model (FMM) was implemented to find a best distribution parameter to characterize the observations. With this technique, after the optimum number of mixtures was identified, those clusters were assigned to various observations. However, previous studies mostly employed just the finite mixture model (FMM), with various distributions, to account for unobserved heterogeneity. The problem with the FMM approach is that it results in a loss of information: for instance, it would come up with N number of equations, where each result would use only part of the whole dataset. On the other hand, some studies used a subjective hierarchy to account for the heterogeneity in the dataset, such as the effect of seasonality or highway system; however, those subjective hierarchies might not account for the optimum heterogeneity in the dataset. Thus, we implement a new methodology, the Bayesian Hierarchical Finite Mixture (BHFMM) to employ the FMM without losing information, while also accounting for the heterogeneity in the dataset, by considering objective and unbiased hierarchies. As the Bayesian technique has the shortcoming of labeling the observations due to label switching; the FMM parameters were estimated by maximum likelihood technique. Results of the identified model were converted to an equation for implementation of machine learning techniques. The heights were optimized to an optimal value and the EPDO was predicted based on the changes. The results of the cost–benefit analysis indicated that after spending about 4 million dollars, the WYDOT would not only recover the expenses, but could also expect to save more than $4 million additional dollars through traffic barrier crash reduction.

The Use of Cost-Benefit Analysis for Evaluating Efficiency of Public Investment Projects (The Case of Sochi-2014 Winter Olympic Games)

2011 ◽  
pp. 57-78
Author(s):  
I. Pilipenko
Keyword(s):  
Net Present Value ◽  
Olympic Games ◽  
Cost Benefit Analysis ◽  
Public Investment ◽  
Cost Benefit ◽  
Investment Efficiency ◽  
Benefit Analysis ◽  
Step Method ◽  
Investment Projects ◽  
The Usa

The paper analyzes shortcomings of economic impact studies based mainly on input- output models that are often employed in Russia as well as abroad. Using studies about sport events in the USA and Olympic Games that took place during the last 30 years we reveal advantages of the cost-benefit analysis approach in obtaining unbiased assessments of public investments efficiency; the step-by-step method of cost-benefit analysis is presented in the paper as well. We employ the project of Sochi-2014 Winter Olympic and Paralympic Games in Russia to evaluate its efficiency using cost-benefit analysis for five accounts (areas of impact), namely government, households, environment, economic development, and social development, and calculate the net present value of the project taking into account its possible alternatives. In conclusion we suggest several policy directions that would enhance public investment efficiency within the Sochi-2014 Olympics.

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