Evaluation of spatio-temporal microsimulation systems

Pappalardo L., Rinzivillo S., Christine K., Kochan B., May M., Schulz D., Simini F.

Human Mobility  Network Science  Data Mining 

The increasing expressiveness of spatio-temporal microsimulation systems makes them attractive for a wide range of real world applications. However, the broad field of applications puts new challenges to the quality of microsimulation systems. They are no longer expected to reflect a few selected mobility characteristics but to be a realistic representation of the real world. In consequence, the validation of spatio-temporal microsimulations has to be deepened and to be especially moved towards a holistic view on movement validation. One advantage hereby is the easier availability of mobility data sets at present, which enables to validate many different aspects of movement behavior. However, these data sets bring their own challenges as the data may cover only a part of the observation space, differ in its temporal resolution or be not representative in all aspects. In addition, the definition of appropriate similarity measures, which capture the various mobility characteristics. The goal of this chapter is to pave the way for a novel, better and more detailed evaluation standard for spatio-temporal microsimulation systems. The chapter collects and structures various aspects that have to be considered for the validation and comparison of movement data. In addition, it assembles the state-of-the-art of existing validation techniques. It concludes with examples of using big data sources for the extraction and validation of movement characteristics outlining the research challenges that have yet to be conquered.

Source: Data Science and Simulation in Transportation Research, edited by Davy Janssens, Ansar-Ul-Haque Yasar, Luk Knapen, pp. 141–146. Hershey: IGI Global, 2014

Publisher: IGI Global, Hershey, USA

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