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Deep Learning based Street Parking Sign Detection and Classification for Smart Cities

Smart traffic management is essential for smart cities. Detection and classification of traffic signs is essential in autonomous driving and in helping with traffic navigation in general. Automated recognition of street parking signs, however, is a more challenging task, due to their small size and huge diversity. Identification of street parking signs is not only helpful in autonomous driving but also in notifying drivers of available parking spaces ahead, significantly alleviating traffic congestion. In this paper, we introduce a new street parking sign detection and classification method that is based on a deep learning network that receives a video feed from a car camera to accurately detect and classify different street parking signs in real-time. Performance evaluations showed that our model achieves mean average precision of 98.56%.