Fatality rates for crashes involving heavy vehicles on highways: A random parameter tobit regression approach

Islam, Mouyid Bin; Hernández, Salvador

doi:10.1080/19439962.2015.1027071

Cited by 24 publications

(21 citation statements)

References 32 publications

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“…Ignoring this inherent variability could lead to incorrect inferences and may lead to a bias in parameter estimates. To address this, researchers have proposed developing random parameter Tobit models to analyze collision rates and to overcome this limitation [30,[35][36][37][38][39][40][41]. More recent studies have also attempted to account for the correlation between collision severities by developing multivariate Tobit models.…”

Section: Methodsmentioning

confidence: 99%

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Ibrahim¹,

Sayed

2021

Sustainability

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The Data Driven Approaches to Crime and Traffic Safety approach identifies opportunities where a single enforcement deployment can achieve multiple objectives: reduce collision and crime rates. Previous research focused on modeling both events separately despite evidence suggesting a high correlation. Additionally, there is a limited understanding of the impact of Mobile Automated Enforcement (MAE) on crime or the impact of changing a deployment strategy on collision and crime dates. For this reason, this study categorized MAE deployment into three different clusters. A random-parameter multivariate Tobit model was developed under the Bayesian framework to understand the impact of changing the deployment on collision and crime rates in a neighborhood. Firstly, the results of the analysis quantified the high correlation between collision and crime rates (0.86) which suggest that locations with high collision rates also coincide with locations with high crime rates. The results also demonstrated the safety effectiveness (i.e., reduced crime and collision rates) increased for the clusters that are associated with an increased enforcement duration at a neighborhood level. Understanding how changing the deployment strategy at a macro-level affects collision and crime rates provides enforcement agencies with the opportunity to maximize the efficiency of their existing resources.

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Section: Methodsmentioning

confidence: 99%

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Ibrahim¹,

Sayed

2021

Sustainability

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“…Many researches investigated the factors contributing to severity of truck-involving crashes for freeway and other types of highway. The main variables studied in the previous researches include roadway characteristics, 2 temporal characteristics, environmental factors, vehicle characteristics, human factors, collision characteristics, occupant characteristics, and traffic conditions. [3][4][5][6][7] Influential factors are more or less different between trucks and passenger cars.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ordered probit model is supposed that the error follows normal distribution. The general specification is given in equation (2)…”

Section: Ordered Probit Modelmentioning

confidence: 99%

Analysis of truck-related crashes of freeways in China

Jiang

Zhao

et al. 2019

Advances in Mechanical Engineering

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Truck-related crashes result in tremendous lives and property loss and become a serious safety issue in China. The goal of this article is to identify the influential factors for severity of truck-related crashes using data from Jingjintang freeways in China and to design an ordered probit model to explore their relationship. Records including crashes, traffic flow attributes, and geometric design features ranging from 2009 to 2012 were collected from Jingjintang freeway. Crashes are divided into three severity levels: slight injury, injury, and fatal injury. The injury crashes is ranking the first place occupying 64.37%. Truck-related crashes are likely to occur when truck percentage is around 20% and 80%. The speed of traffic flow decreases with the more appearance of trucks. The ordered probit model is developed to estimate the impacts of influential factors on injury severity of truck-related crashes. Marginal effects for each level of injury severity are calculated. The results reveal that truck-involving crashes are highly sensitive to factors such as time of day, truck percentage, average slope, operating speed, speed difference, and exposure variable. The average slope of road segment and speed gaps has the greatest impact on all severity levels of crashes.

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“…Furthermore; forklifts, pallet trucks and lifting equipment such as mobile cranes, conveyors, hazardous chemicals, unsafe rack and stacking methods, unsuitable platform applications, improper electrical and ventilation systems, manual lifting and carrying works, workload, lack of education are among the leading reasons of occupational accidents. In maritime transport works; crane, forklift accidents and material strike or overthrow accidents are also widely encountered (Kristiansen, 2013;Islam and Hernandez, 2016;Liu and Moini, 2015;Yu et al, 2014).…”

Section: Severity Of Accidents In Coal Mining Construction and Transmentioning

confidence: 99%

Evaluation of safety trends in construction, mining and transportation sectors in Turkey

Yılmaz

Tosun

2018

Sigurnost (Online)

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SUMMARY: Production processes in construction, mining and transportation involves high risks of occupational accidents all over the world. In 2014, 25.6% of the total accidents and 65% of fatal accidents occured in these three sectors in Turkey. According to the Eurostat data, in 2014, 20% of all work-related accidents and 38% of fatal accidents have occurred in these sectors in EU. The fatality rates in Turkey are very high compared to EU countries. In Turkey, these sectors have high accident risks due to its production processes, use of low-tech, negative conditions and labor-intensive characteristics. Production machines are old, and protective-preventive services are inadequate. Especially in the construction sector, unregistered labor and subcontracting is widespread. Labor inspection is inadequate. In EU accession process, legislative works done in the field of health and safety in Turkey in recent years have not been enough. New regulations were introduced related to protective-preventive services, risk assessment, information and education workers. Nevertheless, occupational accidents has not decreased at the desired level. This paper contains a comperative and statistical analysis of accidents in coal mining, construction and transportation sectors in Turkey and EU. The official statistics data are used in the EU and Turkey. To prevent accidents, action plans must be prepared for each of the three sectors. Practices must be determined and followed strictly within the frame of these action plans

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Fatality rates for crashes involving heavy vehicles on highways: A random parameter tobit regression approach

Cited by 24 publications

References 32 publications

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Using Bayesian Tobit Models to Understand the Impact of Mobile Automated Enforcement on Collision and Crime Rates

Analysis of truck-related crashes of freeways in China

Evaluation of safety trends in construction, mining and transportation sectors in Turkey

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