@conference {1291,
	title = {Weak nodes detection in urban transport systems: Planning for resilience in Singapore},
	booktitle = {2018 IEEE 5th international conference on data science and advanced analytics (DSAA)},
	year = {2018},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The availability of massive data-sets describing human mobility offers the possibility to design simulation tools to monitor and improve the resilience of transport systems in response to traumatic events such as natural and man-made disasters (e.g., floods, terrorist attacks, etc. . . ). In this perspective, we propose ACHILLES, an application to models people{\textquoteright}s movements in a given transport mode through a multiplex network representation based on mobility data. ACHILLES is a web-based application which provides an easy-to-use interface to explore the mobility fluxes and the connectivity of every urban zone in a city, as well as to visualize changes in the transport system resulting from the addition or removal of transport modes, urban zones, and single stops. Notably, our application allows the user to assess the overall resilience of the transport network by identifying its weakest node, i.e. Urban Achilles Heel, with reference to the ancient Greek mythology. To demonstrate the impact of ACHILLES for humanitarian aid we consider its application to a real-world scenario by exploring human mobility in Singapore in response to flood prevention.},
	doi = {10.1109/DSAA.2018.00061},
	url = {https://ieeexplore.ieee.org/abstract/document/8631413/authors$\#$authors},
	author = {Ferretti, Michele and Barlacchi, Gianni and Luca Pappalardo and Lucchini, Lorenzo and Lepri, Bruno}
}
