RFTraffic: Passive traffic awareness based on emitted RF noise from the vehicles

In this paper, a new traffic monitoring technique is introduced which works based on the emitted RF noise from the vehicles. In comparison with the current traffic sensing systems, our light-weight technique has simpler structure in both terms of hardware and software. An antenna installed to the roadside receives the signal generated during electrical activity of the vehicles' sub-systems. This signal feeds the feature extraction and classification blocks which recognize different classes of traffic situation in terms of density and flow. Different classifiers like Naive Bayes, Decision Tree and k-Nearest Neighbor are applied in real-world scenarios and performances higher than 95% are reported. Although the electrical noises of the various vehicles do not have the same statistical characteristics, experimental analysis shows that they are applicable for traffic monitoring goals. Due to the acceptable classification results and the differences between the proposed and current traffic monitoring techniques in terms of interfering factors, advantages and disadvantages, we propose it to work in parallel with the current systems to improve the coverage and efficiency of the traffic control network.