Quantitative network analysis for passenger pattern recognition: An analysis of railway stations

Abstract

As recent attacks in trains and train stations show, the protections of such critical infrastructure plays a major role for public decision makers. Thereby, security installations in the railway network are a frequently discussed topic. Especially the need for an open system demands for technologies that do not influence or delay passenger flows. This also leads to the question of optimal placement of security installations such as smart camera systems or stand-off detectors. For answering this question we observed passenger flows in the Munich central station. The observation data was transferred into a quantitative network and analyzed using various measures. With its help, critical parameter constellations can be identified and investigated in detail. Furthermore we are able to identify special groups of passengers and the differences in their behavior.