adjacent possible air traffic complex network complexity complex_networks complex_systems creativity cuskley data_compression dynamical_systems evolutionary_dynamics gravino information_theory innovation_dynamics kreyon language_dynamics language_games local optimization loreto monechi opinion_dynamics phylogeny relevant_literature servedio social_dynamics statistical_physics techno_social_systems tria XTribe zippers
2015 |
Mastroianni, Pierpaolo; Monechi, Bernardo; Liberto, Carlo; Valenti, Gaetano; Servedio, Vito DP; Loreto, Vittorio Local Optimization Strategies in Urban Vehicular Mobility (Journal Article) PloS one, 10 (12), pp. e0143799, 2015. (Abstract | Links | BibTeX | Tags: GPS data, human mobility, kreyon, local optimization, loreto, monechi, servedio, urban network) @article{Mastroianni2015, title = {Local Optimization Strategies in Urban Vehicular Mobility}, author = {Pierpaolo Mastroianni and Bernardo Monechi and Carlo Liberto and Gaetano Valenti and Vito DP Servedio and Vittorio Loreto}, url = {http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0143799}, doi = {doi:10.1371/journal.pone.0143799}, year = {2015}, date = {2015-12-15}, journal = {PloS one}, volume = {10}, number = {12}, pages = {e0143799}, publisher = {Public Library of Science}, abstract = {The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints—physical, environmental, social, economic—that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy) district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.}, keywords = {GPS data, human mobility, kreyon, local optimization, loreto, monechi, servedio, urban network}, pubstate = {published}, tppubtype = {article} } The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints—physical, environmental, social, economic—that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy) district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions. |
2014 |
Bernardo Monechi Vito DP Servedio, Vittorio Loreto Complex Networks and Transport Systems: Application to Air Transport and Urban Mobility (PhD Thesis) "Sapienza" University of Rome, 2014. (Abstract | Links | BibTeX | Tags: air traffic, big data, complex network, GPS data, human mobility, local optimization, loreto, monechi, servedio, transportation network) @phdthesis{MonechiPhDThesis2014, title = {Complex Networks and Transport Systems: Application to Air Transport and Urban Mobility}, author = {Bernardo Monechi, Vito DP Servedio, Vittorio Loreto}, url = {http://www.phys.uniroma1.it/fisica/sites/default/files/DOTT_FISICA/MENU/03DOTTORANDI/TesiFin27/Monechi.pdf}, year = {2014}, date = {2014-12-20}, address = {Piazzale Aldo Moro 5, 00185, Roma (RO), Italy}, school = {"Sapienza" University of Rome}, abstract = {This thesis is devoted to the study of transportation systems by means of Complex Systems and Complex Network Theories. Complex Networks are a tools of inestimable value in human transportation studies since in most of the cases the means of transportation used by individuals to move in space are bounded to move on a complex network. The topological properties of transportation networks can influence both the ability of individuals to move as well as their behavior in the environment, thus a characterization of the network is mandatory in order to understand the properties of the considered system. The two transportation systems that have been studied in this work are the Air Transport System and the mobility of cars in a urban environment. The analysis and modeling of the Air Transport System is the first and most extensive part of this thesis. In particular we will try to characterize and study the networks in which aircraft fly, exploiting these results to build a data-driven model of Air Traffic Control. The second part of the thesis is a continuation of the studies performed during by Pierpaolo Mastroianni during his Master Thesis. His work concerned the analysis of GPS tracks data in the City of Rome and the inference of statistical laws characterizing the behavior of car drivers. My contribution to his work is the development of a model capable of explaining some of the results presented in the Master Thesis.}, keywords = {air traffic, big data, complex network, GPS data, human mobility, local optimization, loreto, monechi, servedio, transportation network}, pubstate = {published}, tppubtype = {phdthesis} } This thesis is devoted to the study of transportation systems by means of Complex Systems and Complex Network Theories. Complex Networks are a tools of inestimable value in human transportation studies since in most of the cases the means of transportation used by individuals to move in space are bounded to move on a complex network. The topological properties of transportation networks can influence both the ability of individuals to move as well as their behavior in the environment, thus a characterization of the network is mandatory in order to understand the properties of the considered system. The two transportation systems that have been studied in this work are the Air Transport System and the mobility of cars in a urban environment. The analysis and modeling of the Air Transport System is the first and most extensive part of this thesis. In particular we will try to characterize and study the networks in which aircraft fly, exploiting these results to build a data-driven model of Air Traffic Control. The second part of the thesis is a continuation of the studies performed during by Pierpaolo Mastroianni during his Master Thesis. His work concerned the analysis of GPS tracks data in the City of Rome and the inference of statistical laws characterizing the behavior of car drivers. My contribution to his work is the development of a model capable of explaining some of the results presented in the Master Thesis. |