In order to alleviate the increasing number of vehicles every year and make traffic congestion become more and more serious; an intelligent networked vehicle safety detection mechanism based on deep learning is proposed. Intelligent traffic management can effectively alleviate traffic congestion, and vehicle detection is an important part of intelligent transportation implementation. Traditional vehicle detection methods are inefficient and also rely on manual operation, and have poor robustness. Vehicle detection based on deep learning can solve the above problems well. The results show that with the training, box_loss, obj_loss and cls_loss all approach zero. The model can accurately detect the vehicles on the way, and mark the vehicles with boxes, with a high confidence level between 0.69 and 0.88.