PITS: An Intelligent Transportation System in pandemic times

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URI: http://hdl.handle.net/10498/27426
DOI: 10.1016/j.engappai.2022.105154
ISSN: 0952-1976
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2022-09Department
Ingeniería InformáticaSource
Engineering Applications of Artificial Intelligence, Vol. 114Abstract
The control of the pandemic caused by SARS-CoV-2 is a challenge for governments all around the globe.
To manage this situation, countries have adopted a bundle of measures, including restrictions to population
mobility. As a consequence, drivers face with the problem of obtaining fast routes to reach their destinations.
In this context, some recent works combine Intelligent Transportation Systems (ITS) with big data processing
technologies taking the traffic information into account. However, there are no proposals able to gather the
COVID-19 health information, assist in the decision-making process, and compute fast routes in an all-in-one
solution. In this paper, we propose a Pandemic Intelligent Transportation System (PITS) based on Complex
Event Processing (CEP), Fuzzy Logic (FL) and Colored Petri Nets (CPN). CEP is used to process the COVID-19
health indicators and FL to provide recommendations about city areas that should not be crossed. CPNs are
then used to create map models of health areas with the mobility restriction information and obtain fast routes
for drivers to reach their destinations. The application of PITS to Madrid region (Spain) demonstrates that this
system provides support for authorities in the decision-making process about mobility restrictions and obtain
fast routes for drivers. PITS is a versatile proposal which can easily be adapted to other scenarios in order to
tackle different emergency situations.
Subjects
Colored Petri ne; Complex event processing; Fuzzy logic; Intelligent transportation system; PandemicCollections
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