Application of Smeed's formula to assess development of traffic safety in Jordan

Gharaybeh, Fouad A

doi:10.1016/0001-4575(94)90074-4

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…Jacobs [18] repeated this analysis for a number of developed and developing countries using data between 1968 and 1975 and obtained values of 0.000204 and −0.84 for α and β respectively. Gharaybeh [13] applied Smeed's formula to assess the development of road safety in Jordan, relative to that of other middle-eastern and developing countries. In this paper, Eq.…”

Section: Methodsmentioning

confidence: 99%

“…A macroscopic roadsafety model commonly used in the late 60s was proposed by Smeed [33] linking the number of fatalities with the number of vehicles and the population. Jacobs [18] repeated this analysis for a number of developed and developing countries using data between 1968 and 1975 while Gharaybeh [13] applied the same formula to assess the development of road safety in Jordan, relative to that of other middle-eastern and developing countries.…”

Section: Introductionmentioning

confidence: 99%

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Autoregressive nonlinear time-series modeling of traffic fatalities in Europe

Yannis

Antoniou

Papadimitriou

2011

Eur. Transp. Res. Rev.

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Purpose The objective of this paper is to provide a parsimonious model for linking motorization level with the decreasing fatality rates observed across EU countries during the last three decades. Methods A macroscopic analysis of road-safety in Europe at the country level is proposed through the application of non-linear models correlating fatalities and vehicles for the period between 1970 and 2002. Given the time series nature of road safety data, these models result in auto-correlated residuals, thus violating at least one of the assumptions of non-linear regression. Autoregressive forms of the considered models that overcome these limitations and provide superior predictive capabilities are also considered. Results An autoregressive log-transformed model seems to outperform the base autoregressive non-linear model in this respect. The use of these models allowed for the identification of the best and worst performing countries. Conclusions The proposed models can prove useful for assessing the road safety performance of the examined countries, as well as for obtaining some insight on the current and future trends of less developed countries.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Autoregressive nonlinear time-series modeling of traffic fatalities in Europe

Yannis

Antoniou

Papadimitriou

2011

Eur. Transp. Res. Rev.

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“…Further, despite Garber and Hoel (1988) proposing recommended ranges for what constitutes high severity index weighted values (i.e., 9-12 for crash-related death, 3-5 for injury, and 1 for property damage), ETAN is mostly applied subjectively. Gharaybeh (1994) applied ETAN's equation to assess the development of traffic safety in Jordan. He designated the weighted value of 9.5 for fatality, 3.5 for injury, and 1 for property damage in the severity index.…”

Section: Weighted Crash Severity Indexmentioning

confidence: 99%

“…The Equivalent Traffic Accident Number (ETAN), a linear equation, is the most common approach used in weighting the road traffic severity index presented in Equation (Agent and Deen 1974; Gharaybeh 1994). The equation consists of three parameters – total fatality, major and minor injuries, and property damage – with the weighting values distributed amongst them.…”

Section: Weighted Crash Severity Indexmentioning

confidence: 99%

Geographical epidemiology of road safety in Nigeria: The importance of weighted accident severity risk index in spatiotemporal analysis and injury epidemiology

Iyanda¹

2021

Int Social Sci J

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Road safety is an essential indicator of quality of life. This study compared the Chand and Alex severity index with the Equivalent Traffic Accident Number's (ETAN) severity index to understand the spatiotemporal pattern of road traffic crashes in Nigeria. Weighting road crash data could help mitigate road crash risk and improve road safety measures. The weighted crash ratios were calculated based on crash data available between 2012 and 2016. Six factors identified from the literature were used as denominators in deriving these ratios. The sum ratios were ranked and mapped for cross‐temporal examination. There was no significant difference between the two methods for assessing accident severity index in this study. Univariate and multivariate spatial analyses were used to detect the hotspot of the weighted crash severity index (WCSI) for the end of the study period. Only the pairwise comparison analysis found a significant difference between the 2012 and 2016 WCSI (p < 0.05). Multivariate regression identified significant associations between youth literacy, speed violation, tyre blowout, and weighted severity index. Geographically weighted regression indicates that their local effects vary across spatial units. Information obtained from this study is essential for developing strategies towards achieving safe roads in Nigeria and contributes to injury epidemiology research.

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“…Broughton [25] validated the empirical relationship between SE (Sameed's equation) and other developed models on the basis of SE to provide common methods for predicting fatality and accident totals. Gharaybeh [26] researched the development of traffic safety in Jordan over the last two decades, using Smeed's Formula. Navin et al [27] developed a road safety model that includes special cases of the Smeed's model.…”

Section: Related Studiesmentioning

confidence: 99%

An Artificial Neural Network Model for Road Accident Prediction: A Case Study of a Developing Country

Ogwueleka¹,

Misra

Ogwueleka

et al. 2014

APH

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Road traffic accidents (RTA) are one of the major root causes of the unnatural loses of human beings all over the world. Although the rates of RTAs are decreasing in most developed countries, this is not the case in developing countries. The increase in the number of vehicles and inefficient drivers on the road, as well as to the poor conditions and maintenance of the roads, are responsible for this crisis in developing countries. In this paper, we produce a design of an Artificial Neural Network (ANN) model for the analysis and prediction of accident rates in a developing country. We apply the most recent (1998 to 2010) data to our model. In the design, the number of vehicles, accidents, and population were selected and used as model parameters. The sigmoid and linear functions were used as activation functions with the feed forward-back propagation algorithm. The F. N. Ogwueleka et al. An Artificial Neural Network Model for Road Accident Prediction: A Case Study of a Developing Country-178-performance evaluation of the model signified that the ANN model is better than other statistical methods in use.

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Application of Smeed's formula to assess development of traffic safety in Jordan

Cited by 8 publications

References 8 publications

Autoregressive nonlinear time-series modeling of traffic fatalities in Europe

Autoregressive nonlinear time-series modeling of traffic fatalities in Europe

Geographical epidemiology of road safety in Nigeria: The importance of weighted accident severity risk index in spatiotemporal analysis and injury epidemiology

An Artificial Neural Network Model for Road Accident Prediction: A Case Study of a Developing Country

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