Interactive person path analysis in reconstructed public buildings

The behavior of a large number of persons in big buildings is pretty difficult to predict. Long time observations have to be made and many things have to be tested in the real environment, for example how to route people around locked escalators, how to place vending or ticket machines, or how to place various kinds of advertisements. A lot of experience is needed to make the right decisions and mistakes and omissions can easily happen. Models of buildings and simulations can improve the analysis of such environments where many people move about. A good visualization of human behavior in these models can be a great help in planning and improve the quality of necessary changes. It is also possible to analyze the focus of persons who are wandering around in the building, before performing actual changes and thus judge the impact of various alternatives. A major problem is that for most buildings no adequate 3D models to perform such visualizations exist. Current building models need modeling experts for manipulation, and current simulation software needs simulation experts for analyzing movement of people within a building. Ideally, simulated movement of people should be presented in a recognizable 3D model in such a way that it can be easily identified and interpreted without further explanation. It should also be possible to manipulate the building and automatically trigger the changed simulation in the background, without being an expert. This should make it possible to explore alternative planning scenarios and improve the applicability of an envisioned planning tool. This paper presents a way to create an indoor person behavior visualization shown in its application to railway stations. The models are based on a combination of image based reconstruction and existing models of public buildings. The possibility to easily change the environment on the fly creates many possibilities to analyze alternative places for advertisement, vending and ticket machines. Therefore experiments on the real environment can be avoided to save a lot of time and money and increase customer satisfaction.