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Snow and ice is one of the main problems affecting road safety in winter. In order to effectively remove the snow and ice of covering the pavement, the deicing property of asphalt mixture pavement containing steel wool fiber was introduced and investigated by electromagnetic induction heating. Based on the deicing mechanism of Faraday’s law of electromagnetic induction and the Joule’s law, the influences factors affecting deicing efficiency, including length and content of steel wool fiber, ice thickness, output current and ambient temperature were analyzed. Meanwhile, the grey correlation entropy analysis and t-test between the average deicing rate and various influencing factors were explored. BP neural network prediction models of predicting change laws of average deicing rate under different influencing factors were established. The results indicate that the average deicing rate of asphalt mixture adding steel wool fiber increases with the increase of length and content of steel wool fiber. The influence degree of each factor for the average deicing rate is in order as follows: steel wool fiber content, steel wool fiber length, output current, ambient temperature and ice thickness. BP neural network has high accuracy in predicting average deicing rate under various influencing factors and the better simulation results. It is of significance to apply the technology of “electromagnetic induction heating & steel wool fiber” to the efficient deicing of asphalt pavement.

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