Abstract
Natural disasters such as flooding and snow blizzards have evolved from a relatively rare event to a recurring concern for stakeholders, policy makers, and citizens. A special place in this debate is held by the transportation infrastructure; it provides services crucial to a society, and it can yield positive effects to the overall economy due to its interrelation with the urban activities. Finally, due to the increasing trend of urbanization, people are having an increasing dependence on urban transportation.
Consequently, extreme weather conditions could severely impact not only the operation of the transportation infrastructure (network and means) but also the economic activity of a city. Hence, there is the need for a framework that will allow decision-makers, on the one hand, to monitor in real time the status of the transportation network and on the other hand offer them insights on how a critical event, such as a flooding, could affect it before it does.
The purpose of this paper is to present such a tool that allows for efficient and effective monitoring of the status of the transportation network and crisis management in the case of a flooding.
To achieve the objective, two methodological frameworks will be combined: data analytics and simulation. Floating car data (FCD) from a fleet of taxis in the city of the Thessaloniki offer a glimpse on the status of the transportation network. The KPIs that are produced from the data are used as an input to a simulation model. The model has been developed with the methodology of system dynamics, because it allows for the adequate representations of complex systems (such as the transportation infrastructure), it offers a top-down view on the behavior of the system over time, and it can be easily communicated to non-experts.
The model also simulates the physical process of rain and snow, and the user can define how much rain and snow and at which times of the day it will fall. The water accumulates in the road network affecting the speed of the vehicles, and the larger the amount of water the more difficult it is for the sewage system to remove it, thus resulting in flooding roads.
Several scenarios were simulated, mainly trying to capture the dynamics of sudden rainfall and flooding. The results illustrate that there is a disproportional delay between the time that the rain stops and the time it is required for the system to bounce to an equilibrium.
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Tsaples, G., Grau, J.M.S., Aifadopoulou, G., Tzenos, P. (2021). A Simulation Model for the Analysis of the Consequences of Extreme Weather Conditions to the Traffic Status of the City of Thessaloniki, Greece. In: Kotsireas, I.S., Nagurney, A., Pardalos, P.M., Tsokas, A. (eds) Dynamics of Disasters. Springer Optimization and Its Applications, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-030-64973-9_16
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