NEURAL NETWORK BASED VEHICULAR LOCATION PREDICTION MODEL FOR COOPERATIVE ACTIVE SAFETY SYSTEMS

作者：Dorterler Murat^*; Bay Omer Faruk

来源：Promet-Traffic & Transportation, 2018, 30(2): 205-215.

DOI：10.7307/ptt.v30i2.2500

• cooperative active safety systems
• inter-vehicular communication
• vehicular location prediction
• artificial neural networks

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.

• 出版日期2018