An artificial intelligent approach to traffic accident estimation: Model development and application
Yükleniyor...
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Vilnius Gediminas Tech Univ
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study proposes an Artificial Neural Network (ANN) model and a Genetic Algorithm (GA) model to estimate the number of accidents (A), fatalities (F) and injuries (I) in Ankara, Turkey, utilizing the data obtained between 1986 and 2005. For model development, the number of vehicles (N), fatalities, injuries, accidents and population (P) were selected as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with the feed forward-back propagation algorithm. In the GA approach, two forms of genetic algorithm models including a linear and an exponential form of mathematical expressions were developed. The results of the GA model showed that the exponential model form was suitable to estimate the number of accidents and fatalities while the linear form was the most appropriate for predicting the number of injuries. The best fit model with the lowest mean absolute errors (MAE) between the observed and estimated values is selected for future estimations. The comparison of the model results indicated that the performance of the ANN model was better than that of the GA model. To investigate the performance of the ANN model for future estimations, a fifteen year period from 2006 to 2020 with two possible scenarios was employed. In the first scenario, the annual average growth rates of population and the number of vehicles are assumed to be 2.0 % and 7.5%, respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.60, which represents approximately two and a half-fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for road safety applications.
Açıklama
AKGUNGOR, ALI PAYIDAR/0000-0003-0669-5715; DOGAN, Erdem/0000-0001-7802-641X
Anahtar Kelimeler
accident prediction model, artificial neural network (ANN), genetic algorithm, injury, Ankara
Kaynak
Transport
WoS Q Değeri
Q1
Scopus Q Değeri
Q2
Cilt
24
Sayı
2
Künye
Akgüngör, A. P., & Doğan, E. (2009). An artificial intelligent approach to traffic accident estimation: Model development and application. Transport, 24(2), 135-142. https://doi.org/10.3846/1648-4142.2009.24.135-142
