- Tytuł:
- Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers
- Autorzy:
-
Ghasemlou, K.
Aydi, M. M.
Yildirim, M. S. - Powiązania:
- https://bibliotekanauki.pl/articles/223654.pdf
- Data publikacji:
- 2015
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
traffic accidents
cyclist
pedestrians
artificial linear network
regression trees
multiple linear
wypadki drogowe
rowerzysta
piesi - Opis:
- Accident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Instıtute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.
- Źródło:
-
Archives of Transport; 2015, 34, 2; 29-35
0866-9546
2300-8830 - Pojawia się w:
- Archives of Transport
- Dostawca treści:
- Biblioteka Nauki
Artykuł