baldassarri baronchelli barrat caglioti castellano cattuto complexity dattoli evolutionary_dynamics granular_media granular_media herrmann information_theory innovation_dynamics kreyon language_dynamics loreto mari mukherjee petri pietronero puglisi quantum_optics self_organization servedio statistical_physics techno_social_systems tria zapperi 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 | Tag: 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. |
Bernardo Monechi, Vito DP Servedio ; Loreto, Vittorio Congestion Transition in Air Traffic Networks Journal Article PLoS ONE, 10 (5), pp. e0125546, 2015. Abstract | Links | BibTeX | Tag: air traffic, complex_systems, loreto, monechi, servedio, transportation networks @article{Monechi2015, title = {Congestion Transition in Air Traffic Networks}, author = {Bernardo Monechi, Vito DP Servedio and Vittorio Loreto}, url = {http://dx.doi.org/10.1371%2Fjournal.pone.0125546}, doi = {10.1371/journal.pone.0125546}, year = {2015}, date = {2015-05-20}, journal = {PLoS ONE}, volume = {10}, number = {5}, pages = {e0125546}, abstract = {Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.}, keywords = {air traffic, complex_systems, loreto, monechi, servedio, transportation networks}, pubstate = {published}, tppubtype = {article} } Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios. |
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 | Tag: 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. |
Bernardo Monechi Vito DP Servedio, Vittorio Loreto An Air Traffic Control Model Based Local Optimization over the Airways Network Inproceedings Schaefer, Dirk (Ed.): Proceedings of the SESAR Innovation Days (2014), EUROCONTROL 2014, ISBN: 978-2-87497-077-1. Abstract | Links | BibTeX | Tag: air traffic, extremal optimization, local optimization, loreto, monechi, servedio, transportation networks @inproceedings{Monechi2014, title = {An Air Traffic Control Model Based Local Optimization over the Airways Network}, author = {Bernardo Monechi, Vito DP Servedio, Vittorio Loreto}, editor = {Dirk Schaefer}, url = {http://www.sesarinnovationdays.eu/sites/default/files/media/SIDs/SID%202014-04.pdf}, isbn = {978-2-87497-077-1}, year = {2014}, date = {2014-11-25}, booktitle = {Proceedings of the SESAR Innovation Days (2014)}, organization = {EUROCONTROL}, abstract = {The introduction of a new SESAR scenario in the European Airspace will impact the functioning and the performances of the current Air Traffic Management (ATM) System. The understanding of the features and the limits of the current system could be crucial in order to improve and design the structure of the future ATM. In this paper we present some results of the "Assessment of Critical Delay Patterns and Avalanche Dynamics” PhD project from the ComplexWorld Network. During this project we developed a model of Air Traffic Control (ATC) based on Complex Network theory capable of reproducing the features of the real ATC in three European National Airspaces. We then developed an optimization algorithm based on “Extremal Optimization” in order to build efficient and globally optimized planned trajectories. The ATC model is applied in order to study the efficiency of this new planned trajectories when subject to external perturbations and to compare them to the current situation.}, keywords = {air traffic, extremal optimization, local optimization, loreto, monechi, servedio, transportation networks}, pubstate = {published}, tppubtype = {inproceedings} } The introduction of a new SESAR scenario in the European Airspace will impact the functioning and the performances of the current Air Traffic Management (ATM) System. The understanding of the features and the limits of the current system could be crucial in order to improve and design the structure of the future ATM. In this paper we present some results of the "Assessment of Critical Delay Patterns and Avalanche Dynamics” PhD project from the ComplexWorld Network. During this project we developed a model of Air Traffic Control (ATC) based on Complex Network theory capable of reproducing the features of the real ATC in three European National Airspaces. We then developed an optimization algorithm based on “Extremal Optimization” in order to build efficient and globally optimized planned trajectories. The ATC model is applied in order to study the efficiency of this new planned trajectories when subject to external perturbations and to compare them to the current situation. |
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