Scaling law of urban individual tour behavior

Abstract: Analysing and modeling urban individual tour behavior are of great significance for a wide range of applications such as transportation management and urban planning. However, the urban tour length distribution has long been neglected in individual mobility models that can be found in recent literature. To fill in this gap, we analyse Foursquare user check-in data and find that urban human tour length distribution follows a power-law with exponential truncation. This law also appears in China's urban heavy truck trajectory data which can reflect commercial vehicle mobility. To reproduce the universal scaling law on tours of urban human and truck mobility, we introduce a tour terminate-continue model. Our model can not only reproduce the urban tour length distribution, but also the Heaps' law and Zipf's law in human and truck mobility, providing a new perspective for characterizing individual human mobility.