Due to the COVID-19 pandemic, the focus on everydays mobility has been shifted from traditional means of transport to how to safely commute for work and/or move around the neighbourhood. Maintaining the safe distance among pedestrian becomes crucial in big pedestrian networks. Looking at personal goals, such as walking through the shortest path, could lead to congestion phenomena on both roads and crossroads violating the imposed regulations. We suggest a centralized multi-objective approach able to assign alternative fair paths for users while maintaining the congestion level as lower as possible. Computational results show that, even considering paths that are not longer than the 1% with respect to the shortest path for each pedestrian, the congestion phenomena are reduced of more than the 50%.

Gathering avoiding centralized pedestrian advice framework: an application for Covid-19 outbreak restrictions

Morandi V
2021-01-01

Abstract

Due to the COVID-19 pandemic, the focus on everydays mobility has been shifted from traditional means of transport to how to safely commute for work and/or move around the neighbourhood. Maintaining the safe distance among pedestrian becomes crucial in big pedestrian networks. Looking at personal goals, such as walking through the shortest path, could lead to congestion phenomena on both roads and crossroads violating the imposed regulations. We suggest a centralized multi-objective approach able to assign alternative fair paths for users while maintaining the congestion level as lower as possible. Computational results show that, even considering paths that are not longer than the 1% with respect to the shortest path for each pedestrian, the congestion phenomena are reduced of more than the 50%.
2021
978-3-030-86286-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/553720
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