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In this paper we analyze the speed profiles on the whole Italian road network. More precisely, using Octo Telematics GPS data (about 3% of the total Italian cars amount) collected during four weeks of May 2011, we have built up for everyday of the week a mean speed profile with a time resolution equal to 15 minutes, obtaining about one million speed profiles. For this research working we developed software able to efficiently navigate the full Italian road network designing its topological properties, and algorithms for traffic control, prevision and governance. Moreover we discovered that a strong correlation function (>90%) represents 96.4% of all data with a reduced number of profiles (256). This work was performed in order to construct an ICT (Information Communication Technology) system for monitoring and managing traffic, with a particular attention to the safety for individual passengers, vehicles and goods.

In the near future a large amount of data on individual vehicle position and speed for the full road network will be available from GPS systems. This possibility opens new research perspectives for prevention and governance of congestion and of traffic criticalities. A prototype model, developed under Pegasus Project sponsored by the Italian Ministry of Industry, is working in Rome. The system is based on the real time reconstruction of the speed, density and flux on the whole metropolitan road network using a low sampling rate GPS data set. We present the state of the art of the project discussing its strength and weakness. We then show the results of the data analysis for the month of May 2010.

Walking is a fundamental activity of human beings. Any simple movement is the result of complex interactions between the external environment and the individual cognitive dynamics. The proposedmodels havemainly considered a deterministic point of view to describe the choice of the pedestrians trajectories and to study the critical congested states. But recently it has been pointed out the importance of the individual free will in determining both the microscopic pedestrian behavior and the emergent properties of the crowd dynamics. In this paper we discuss a hierarchical model for pedestrian mobility whose emergent dynamical properties are determined by the bottom-up and top-down actions among the microscopic-level (free-will level), the mesoscopic level (deterministic level) andmacroscopic level (cognitive level). The "mobbers" have an internal cognitive dynamics, performboth physical and information based interactions using a vision mechanism and are able to compute a cognitive map representation of the geometrical space. The model has been implemented in the DISTRIMOBS simulator that is designed to simulate a whole city on a distributed architecture. The main properties of the model are discussed and some applications are presented.

In this paper we design some characteristics of a possible E-governance system for the urban mobility. In particular we shortly present the complex city features and the background automata gas paradigm for a microscopic modeling. Moreover we show some statistical laws based on long time series of traffic dynamics data, fundamental for the now-casting and the private vehicles mobility control. We study also the crowd dynamics, specifying a stochastic equation founded on a cognitive decisional dynamics, with a threshold changing the evolution from a cooperative behavior to a selfish one, which we identify with the emergence of ‘panic states’. Concluding, essentially our E-governance system is composed of a large data base, of one or more centers that can collect real time microscopic data, elaborate models based on the individual mobility demand, find the optimal self-organized mobility states and diffuse the relative information (best path dynamical map)along the mobility network performing a bidirectional continuous interaction with the citizens. Moreover we underline that the complex interactions via information diffusion, i.e. cognitive based dynamics and mobility governance are low energy consuming

The future Information Communication Technologies will allow the collection of a large amount of data on individual mobility. The data analysis will not only provide information on the human mobility peculiarities, but will also open new possibilities for studying the criticalities of a complex system. In Italy a sample of 2% of the vehicle population is monitored by a GPS system for insurance reason. We have analyzed the data in the metropolitan area of Rome for a whole month (May 2010) to reconstruct an empirical Fundamental Diagram based on the real time reconstruction of the speed, density and flux on the whole road network. The main difficulties are the low sampling rate of GPS data set and the heterogeneity of the road network in the metropolitan area of Rome and of the drivers’ behavior. We present the first results of this research discussing the future perspectives for prevention and governance of traffic congestions.

We present a agent-base model to simulate the citizens mobility in a urban space where different transportation systems are at disposal. The request of mobility is determined by the "chronotopic areas": i.e. urban areas where time-dependent activities are installed and attract the citizens according to their social categories. The core of the model is a decision mechanism for the agents based on a daily program, which chooses the transportation means and the roads to reach the scheduled chronotopic areas. The decision mechanism depends on the social categories of the agents, on the informations at disposal, on the attraction force towards a chronotopos and on some random choices. The daily program can also be upgraded according to the informations given to the agents. The finite volume congestion effects are present in the private transportation and in the finite capacity of the public means whereas the crowding in the chronotopic areas causes the extension of the stay in the areas themselves. Some properties of the model are discussed in the framework of complex systems and the results of simulations on real situations are presented.

Application des systemes dynamiques et statistiques all'evolution urbaine e problemes des modilization dans les systems complexes sociales

We consider the problem of modeling urban mobility using the complex systems key of lecture. We discuss the properties of the Auto-mobilis model, a virtual simulator for private car mobility based on the individual citizen propensities and the existence of "chronotopoi", which are the primary causes of citizens' mobility requests. Auto-mobilis is a microscopic agent-based model that takes into account both the physical interactions and the cognitive dynamics. We present the current status of the project and discuss the applications to real situations. The model assumptions are justified by a comparison with GPS observational data on single vehicle trajectories.