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In this study, the computational development conducted was based on Convolutional Neural Networks (CNNs) and the You Only Look Once (YOLO) algorithm to detect vehicles from aerial images and calculate the safe distance between them on Brazilian highways. Data analysis was performed in a dataset composed of 896 images, recorded on videos by a DJI Spark Drone. Thus, with this dataset, 60% of the images were used for training, 20% for validation and the remaining 20% for tests. Experiments were conducted to detect vehicles in different network architecture configurations, the best result was obtained with the YOLO Full-608, reaching an Average Accuracy (mAP) of 95.6%. The accuracy of the results encourages the development of systems capable of estimating the safe distance between vehicles during their movement on the highways, allowing to detect and minimize the risk of accidents.

Vehicle Speed Detection and Safety Distance Estimation Using Aerial Images of Brazilian Highways