196,367 research outputs found
Towards a Statistical Physics of Human Mobility
In this paper, we extend some ideas of statistical physics to describe the
properties of human mobility. From a physical point of view, we consider the
statistical empirical laws of private cars mobility, taking advantage of a GPS
database which contains a sampling of the individual trajectories of 2% of the
whole vehicle population in an Italian region. Our aim is to discover possible
"universal laws" that can be related to the dynamical cognitive features of
individuals. Analyzing the empirical trip length distribution we study if the
travel time can be used as universal cost function in a mesoscopic model of
mobility. We discuss the implications of the elapsed times distribution between
successive trips that shows an underlying Benford's law, and we study the rank
distribution of the average visitation frequency to understand how people
organize their daily agenda. We also propose simple stochastic models to
suggest possible explanations of the empirical observations and we compare our
results with analogous results on statistical properties of human mobility
presented in the literature
A Tale of Many Cities: Universal Patterns in Human Urban Mobility
The advent of geographic online social networks such as Foursquare, where users voluntarily signal their current location, opens the door to powerful studies on human movement. In particular the fine granularity of the location data, with GPS accuracy down to 10 meters, and the worldwide scale of Foursquare adoption are unprecedented. In this paper we study urban mobility patterns of people in several metropolitan cities around the globe by analyzing a large set of Foursquare users. Surprisingly, while there are variations in human movement in different cities, our analysis shows that those are predominantly due to different distributions of places across different urban environments. Moreover, a universal law for human mobility is identified, which isolates as a key component the rank-distance, factoring in the number of places between origin and destination, rather than pure physical distance, as considered in some previous works. Building on our findings, we also show how a rank-based movement model accurately captures real human movements in different cities
Revisiting the Generality of the Rank-based Human Mobility Model
Location-based social networks, in addition to revealing users' online social network, also informs users' actual movements in the offline physical world. Due to this, they have recently been used in large-scale mobility and urban studies. In this paper, using a rigorous statistical methodology, we have found that a rank-distance distribution, which in recent research has been suggested to be a universal mobility law across cultural, demographic and national boundaries, does not follow a power-law distribution as originally claimed. Using a large-scale dataset obtained from Foursquare in Switzerland and New York City, we have shown that place transitions can be better explained using a log-normal and power-law with exponential cutoff model. Our study suggests that urban mobility patterns are more nuanced than previously reported and that goodness-of-fit tests need to be done in view of the generality of human mobility models
Statistical Laws in Urban Mobility from microscopic GPS data in the area of Florence
The application of Statistical Physics to social systems is mainly related to
the search for macroscopic laws, that can be derived from experimental data
averaged in time or space,assuming the system in a steady state. One of the
major goals would be to find a connection between the statistical laws to the
microscopic properties: for example to understand the nature of the microscopic
interactions or to point out the existence of interaction networks. The
probability theory suggests the existence of few classes of stationary
distributions in the thermodynamics limit, so that the question is if a
statistical physics approach could be able to enroll the complex nature of the
social systems. We have analyzed a large GPS data base for single vehicle
mobility in the Florence urban area, obtaining statistical laws for path
lengths, for activity downtimes and for activity degrees. We show also that
simple generic assumptions on the microscopic behavior could explain the
existence of stationary macroscopic laws, with an universal function describing
the distribution. Our conclusion is that understanding the system complexity
requires dynamical data-base for the microscopic evolution, that allow to solve
both small space and time scales in order to study the transients.Comment: 17 pages, 14 figures .jpg, use imsart.cl
Physicists, stamp collectors, human mobility forecasters
One of the two reviewers studied in high school to be a physicist. In the end, he became something else, but he never lost his awe of physics. The other reviewer never intended to become a physicist, but he sometimes asks himself why he didn’t become one. Today, they are both sociologists who practice their science on an action theory basis and believe that regularities exist in the
world of social actions which can be perceived, understood, explained – and even used for making predictions
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