Dealing with Emergencies: The Case of a Heavy Disruption of the Mexico City Metro System

DOI

10.2991/jrarc.2015.5.3.1How to use a DOI?

Keywords

ANN, Emergency response, Metro system, Megacity

Abstract

The paper presents the results of a forecasting model associated with the affluence of users of the metro line-B of Mexico City's metro system. It also presents in a way a retrospective analysis of the metro incident that occurred on September, 2011, in the same metro line; the incident affected seven metro stations and about 17 thousand commuters. The approach has been the use of Artificial Neural Networks (ANN). The main conclusions may be summarized as follows: (i) the metro incident has illustrated the fact that different modes of urban transport are highly interdependent; (ii) the proposed ANN model has the potentiality to be used to forecasting the affluence of users for any metro line for the case of Mexico City's metro system; (iii) the above (ii) can be used as input to the decision process in order to implement the required number of coaches to assist the affected commuters; (iv) Both (ii) and (iii) should be part of an emergency response plan to mitigate the impact of cascading failures due to interdependencies amongst the different modes of urban transport.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Diego Padilla-Pérez
AU  - Jaime Santos-Reyes
AU  - Samuel Olmos-Peña
PY  - 2015
DA  - 2015/10/31
TI  - Dealing with Emergencies: The Case of a Heavy Disruption of the Mexico City Metro System
JO  - Journal of Risk Analysis and Crisis Response
SP  - 142
EP  - 151
VL  - 5
IS  - 3
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2015.5.3.1
DO  - 10.2991/jrarc.2015.5.3.1
ID  - Padilla-Pérez2015
ER  -