The application of smeed's equation for road accidents in Greece

Pitsiava-Latinopoulou, Magdalini; Tsohos, G

doi:10.1016/0001-4575(82)90002-1

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…Leeming [22] proposed the Smeed's factors for different countries and different years. Pitsiava-Latinapoulou and Tsohos [23] analyzed a 14-year record concerning the relationship between fatal road accidents and the number of registered vehicles in Greece using statistical method and described a relationship that is at a fairly good degree of accuracy by Smeed's equation (SE). Adams [24] examined accident black spot treatment and seat belt legislation on behalf of vehicle safety regulations, benefitting from explanations of Smeed's Law.…”

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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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

View full text Add to dashboard Cite

show abstract

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

Gharaybeh

1994

Accident Analysis & Prevention

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Road Accident Fatalities Forecasting Models using Smeed’s Regression Analysis: A Case Study

Cenaj,

Dervishi

2024

EJENG

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Fatalities and injuries triggered by road traffic accidents are worthwhile traffic safety problems, especially for developing and developed countries. Several academic works have convinced that using data from a given group, a weighty relationship between the number of road traffic fatalities (RTFs) and registered vehicle, population size is designed. This paper uses historical data from over 10 years in Albania to identify the relationship between the same factors. The study divulges that such a relationship cannot be impacted with a good degree of exactness by Smeed's Equation (SE). Additionally, road accident prediction models by the structural form of Smeed’s regression method enable estimating RTFs tied to population size and number of active vehicles. The modified forms of SE are the key to a satisfactory match in predicting RTFs in Albania.

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The application of smeed's equation for road accidents in Greece

Cited by 4 publications

References 2 publications

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

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

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

Road Accident Fatalities Forecasting Models using Smeed’s Regression Analysis: A Case Study

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