The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm

• DOI: 10.3390/electronics11131981
• Publication Date: 2022-06-25T14:39:13Z
• Authors: Feng Guo; Fumin Zou; Sijie Luo; Lyuchao Liao; Jinshan Wu; Xiang Yu; Cheng Zhang
• Keywords: Data set

As one of the largest Internet Things systems in world, China’s expressway electronic toll collection (ETC) generates nearly billion pieces transaction data every day, recording traffic trajectories almost all vehicles on expressway, which has great potential application value. However, there are inevitable missed transactions and false ETC system, leads to certain missing rates data. In this work, a dynamic search step SegrDTW algorithm based an improved DTW is proposed according characteristics with origin–destination (OD) constraints coupling between gantry path vehicle trajectory. Through constructing spatial window segment retrieval, complexity effectively reduced, efficiency abnormal detection greatly improved. real experiments, only needs 3.36 s measure events single set OD for 10 days. Compared mainstream algorithms, performs best. Therefore, proposal provides feasible method event province even whole country.