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Studi Model Prediksi Fatalitas Korban Kecelakaan Lalu Lintas Jalan Berdasarkan Karakteristik Wilayah dengan Multi Variabel

*Supratman Agus  -  Program Studi Teknik Sipil Universitas Pendidikan Indonesia, Indonesia

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Road safety researchers in many countries assume that population and numbers of vehicles as the most decisive variables to predict numbers of fatality by road accidents. That assumption is not accordance with conditions in Indonesian. In ASEAN, Indonesia has largest of area and population, longest road infrastructure, and largest number of motor vehicles, but road victims’ fatality is low. This indicate under reporting. Tis study aimed to obtaining the predictive model of road victims’ fatality which suits Indonesia’s conditions. Three model were compared are Andreassen model, Artificial Neural Network with two variable (ANN2) and four variables (ANN4), with numbers of driving license holder and length of road as two additional variables. Model validation was performed on three cities in West Java with different categories population densities. Result of comparison and validation test using MAPE, MAE, and RMSE criteria show that the best predictions models of road victims’ fatality is ANN4. In addition, predictions of road victim numbers in Indonesia are not only influenced by population and numbers of vehicles, but also by driving license holder numbers and length of road.
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Keywords: Fatality; Model comparison; Andreassen model; Artificial Neural Network (ANN) model

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Last update: 2024-04-20 08:09:36

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