Data-Driven Abnormal Behavior Identification System: A Survey for “In-out” in the Same Subway Station

With the development of subway transportation capacity, “stealing behavior”, “illegal advertising behavior” and “begging behavior” have also emerged in an endless stream. These behaviors have brought negative influence on subway operation and management. The paper will analyze the abnormal data of “In-out” in the same subway station (IOSSS) to explore the abnormal behavior of subway riders with Beijing' riding data. IOSSS refers to passengers' entering and leaving at the same subway station. The study collected half one year' passenger data, analyzed the characteristics of IOSSS, and carried out passenger cluster analysis and portrait analysis. The research can deepen the understanding of IOSSS, analyzed the purpose and characteristics of the abnormal riders, which is conducive to the safety of subway passengers.