Mobility Award winner November 2017

The main topic of my Ph.D. thesis is “Models and measures for traffic in complex urban networks”, that is to approach classical transportation engineering problems through complex networks theory.

Since the earlier period of my Ph.D. I have studied how the topology of an urban network determines the propagation of congestion and, in general, of the traffic flow. Inspired by the comparison of the congested pattern formation and the well-known physical-biological model of reaction-diffusion, we designed a traffic model that simulates the congestion propagation with an adaptive control strategy that requires just sparse online information from the real road network. The main contribute and originality of this model is that it does not need any Origin-Destination trip estimation (OD matrix) neither any other exogenous information than the initial condition. Moreover, the model has been improved with the finding of correlation among the speed profiles of the links of the urban network that allow us to clusterize them and obtain, as consequence, efficient and low-cost data collection effort.

Another topic that I started to explore in the first two years of my Ph.D. has been the definition of a dynamical efficiency for a network affected by congestion. It consists of a general technique that can be applied to each spatial network that experiences a degradation in term of link transmission time. We found that this measure represents an appropriate and application-driven measure in transportation network analysis by classifying the functionality of each road in relation to its neighborhood and its usage. The combination of these results with some perimeter control techniques, already used in transportation engineering, can bring to many applications in real traffic network to mitigate the traffic condition in congested areas.

In collaboration with Prof. V. Latora and his group at Queen Mary University of London, we aim to improve both the traffic model and the definition of the dynamical efficiency and extend them in a multiplex framework, associable with the multi-modality urban transportation system (metro, bus, tram, train, etc.), and simulate the diffusion of the traffic flow and an appropriate index for urban network performances.