RFTraffic: a study of passive traffic awareness using emitted RF noise from the vehicles

In this article, a new traffic sensing and 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 or the inside of a car 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, flow and location. Different classifiers like naive Bayes, Decision Tree and k-Nearest Neighbor are applied in real-world scenarios and performances for instance of traffic situation detection are reported with higher than 95%. Although the electrical noises of the various vehicles do not have the same statistical characteristics, results from two experiments with an implementation on RF receiver illustrate that our approach is practically feasible 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.