Prethodno priopćenje
https://doi.org/10.7307/ptt.v30i2.2500
Neural Network Based Vehicular Location Prediction Model for Cooperative Active Safety Systems
Murat Dörterler
; Gazi University, Faculty of Technology, Department of Computer Engineering
Ömer Faruk Bay
; Gazi University, Faculty of Technology, Department of Electrical - Electronics Engineering
Sažetak
Safety systems detect unsafe conditions and provide warnings for travellers to take action and avoid crashes. Estimation of the geographical location of a moving vehicle as to where it will be positioned next with high precision and short computation time is crucial for identifying dangers. To this end, navigational and dynamic data of a vehicle are processed in connection with the data received from neighbouring vehicles and infrastructure in the same vicinity. In this study, a vehicular location prediction model was developed using an artificial neural network for cooperative active safety systems. The model is intended to have a constant, shorter computation time as well as higher accuracy features. The performance of the proposed model was measured with a real-time testbed developed in this study. The results are compared with the performance of similar studies and the proposed model is shown to deliver a better performance than other models.
Ključne riječi
cooperative active safety systems; inter-vehicular communication; vehicular location prediction; artificial neural networks
Hrčak ID:
200065
URI
Datum izdavanja:
20.4.2018.
Posjeta: 1.210 *