The conducted literature review aimed to provide an overall perspective on the significant findings of past research works related to vehicle crashes and prediction models. The literature review also provided information concerning past road safety research methodology and viable statistical analysis and computing tools. Though the selection of a specific model hinges on the objective of the research and nature of the response, when compared to statistical modeling techniques, Artificial Neural Networks (ANNs), which can model complex nonlinear relationships among dependent and independent parameters, have been witnessed to be very powerful
This paper investigates the use of two well-known artificial neural network (ANN) paradigms: the mul...
Maintaining highway safety is viewed as the over-arching goal of mananging transportation systems at...
Despite the effort of the authorities and researchers, there has been no sign of decreasing in the n...
The conducted literature review aimed to provide an overall perspective on the significant findings ...
Motor vehicle crashes are one of our nation\u27s most serious social, economic and health issues. Th...
Vehicle collisions amount to a significant loss of life in America. Upward of 30,000 lives are lost ...
Vehicle collisions amount to a significant loss of life in America. This study used artificial neura...
One way to reduce road crashes is to determine the main influential factors among a long list that a...
Traffic crashes cause significant loss of life and property across the world. Analyzing transportati...
This paper investigates the use of two well-known artificial neural network (ANN) paradigms: the mul...
The number of accidents on a given highway section during a certain period of time is probabilistic ...
International audienceThe paper focuses on the development of a Risk index model for traffic crash p...
In 2015, about 20% of the 52,231 fatal crashes that occurred in the United States occurred at unsign...
This study proposes a Neural Network (NN) classifier model for predicting crashes on freeways and ar...
Abstract Purpose Over the past 10 years, building on road infrastructure data, crash prediction mode...
This paper investigates the use of two well-known artificial neural network (ANN) paradigms: the mul...
Maintaining highway safety is viewed as the over-arching goal of mananging transportation systems at...
Despite the effort of the authorities and researchers, there has been no sign of decreasing in the n...
The conducted literature review aimed to provide an overall perspective on the significant findings ...
Motor vehicle crashes are one of our nation\u27s most serious social, economic and health issues. Th...
Vehicle collisions amount to a significant loss of life in America. Upward of 30,000 lives are lost ...
Vehicle collisions amount to a significant loss of life in America. This study used artificial neura...
One way to reduce road crashes is to determine the main influential factors among a long list that a...
Traffic crashes cause significant loss of life and property across the world. Analyzing transportati...
This paper investigates the use of two well-known artificial neural network (ANN) paradigms: the mul...
The number of accidents on a given highway section during a certain period of time is probabilistic ...
International audienceThe paper focuses on the development of a Risk index model for traffic crash p...
In 2015, about 20% of the 52,231 fatal crashes that occurred in the United States occurred at unsign...
This study proposes a Neural Network (NN) classifier model for predicting crashes on freeways and ar...
Abstract Purpose Over the past 10 years, building on road infrastructure data, crash prediction mode...
This paper investigates the use of two well-known artificial neural network (ANN) paradigms: the mul...
Maintaining highway safety is viewed as the over-arching goal of mananging transportation systems at...
Despite the effort of the authorities and researchers, there has been no sign of decreasing in the n...