The architecture for vehicular black-box image communication in VANET

Abstract

In this paper, we introduce a new practical and secure architecture for vehicular black-box image communication in a VANET environment. Since black-box images show more detailed descriptions of the vehicle and the ambient conditions, more reliable traffic information and analysis can be provided. The main barrier to establish the black-box image communication system is that the communicational and computational overheads for transferring and processing images are pretty big. In addition, the abuse of black-box images can infringe on the privacy of driver since vehicle's behaviors and driving patterns can be easily exposed from the images. In this paper, we propose an efficient and secure vehicular black-box image communication model. Our proposed model minimizes the communicational and computation overheads by GPS based-key frame extraction and communication technique. In addition, the proposed model, assisted by RSUs, guarantees the reliable use of the images and preserves driver's privacy. We also provide the simulated performance of our model with real black-box images.