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A Review of Learning-Based Traffic Accident Prediction Models and Their Opportunities to Improve Information Security

Abstract:

The World Health Organization (WHO) affirms that the first cause of death for people 5 to 29 years old is traffic accidents. Their victims are not only drivers but also passengers and road users. Therefore, reducing the number of accidents by providing technological advances is fundamental. This study presents the states of the art of traffic accident prediction models based on machine learning and security for connected vehicles. On one hand, it was determined that most of the models are seen as classification problems and are solved using deep learning and neural network algorithms. Also, some issues to be solved such as the integration of spatial heterogeneity or the solution of high dimensionality were identified. On the other hand, recent research has been mainly focused on resolving the security of communication links and identity and liability threats. The authentication into a VANET via digital …