ETC Data Mining Based on Hybrid Markov Model

ETC tolling data contains a vast amount of information. The data mining to improve management efficiency is an urgent problem to the expressway administrations. In this paper, ETC raw data are used to construct the route sequences transactional database. Against the shortcomings of low accuracy and coverage rate with basic Markov route prediction model, a new method based on hybrid Markov route prediction model is proposed to predict vehicle route on the expressway. ETC vehicles' future driving states are predicted and unusual route sequences are detected using this method. The experimental results show that the detecting result is reliable, and the overall prediction accuracy rate is above 83%. It may provide theoretical foundation and decision support for expressway administrations to develop charge checking and improve ETC management level.