Communication devices (mobile networks, social media platforms) are produced digital traces for their users either voluntarily or not. This type of collective data can give powerful indications on their effect on urban systems design and development.
For understanding the collective human behavior of urban city, the modeling techniques could be used. In this study the most important feature of human mobility is considered, which is the radius of gyration . This parameter is used to measure how (far /frequent) the individuals are shift inside specific observed region.
The research objectives are exploring characteristics of human mobility patterns, subsequently modelling them mathematically depending on inter-event time and traveled distances parameters using CDRs (Call Detailed Records). The observations are obta
ined from Armada festival in France. Understanding, modelling and simulating human mobility among urban regions is excitement approach, due to itsimportance in rescue situations for various events either indoor events like evacuation of buildings or outdoor ones like public assemblies,community evacuation in casesemerged during emergency situations, moreover serves urban planning and smart cities.
The communication devices have produced digital traces for their users either voluntarily or not. This type of collective data can give powerful indications that are affecting the urban systems design and development. In this study mobile phone data
during Armada event is investigated. Analyzing mobile phone traces gives conceptual views about individuals densities and their mobility patterns in the urban city. The geo-visualization and statistical techniques have been used for understanding human mobility collectively and individually. The undertaken substantial parameters are inter-event times, travel distances (displacements) and radius of gyration. They have been analyzed and simulated using computing platform by integrating various applications for huge database management, visualization, analysis, and simulation. Accordingly, the general population pattern law has been extracted. The study contribution outcomes have revealed both the individuals densities in static perspective and individuals mobility in dynamic perspective with multi levels of abstraction (macroscopic, mesoscopic, microscopic).
Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. Previous studies proposed a strategy updating mechanism, which successfully demonstrated that the scale-free network can provide a fr
amework for the emergence of cooperation. Instead, individuals in random graphs and small-world networks do not favor cooperation under this updating rule. However, a recent empirical result shows the heterogeneous networks do not promote cooperation when humans play a Prisoners Dilemma. In this paper, we propose a strategy updating rule with payoff memory. We observe that the random graphs and small-world networks can provide even better frameworks for cooperation than the scale-free networks in this scenario. Our observations suggest that the degree heterogeneity may be neither a sufficient condition nor a necessary condition for the widespread cooperation in complex networks. Also, the topological structures are not sufficed to determine the level of cooperation in complex networks.
