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

TL;DR

This paper proposes a centralized multi-objective framework to assign pedestrian paths during COVID-19, effectively reducing congestion while respecting safety and efficiency constraints.

Contribution

It introduces a novel multi-objective approach for fair pedestrian path assignment that minimizes congestion during pandemic restrictions.

Findings

Congestion reduced by over 50% with minimal path length increase.

Paths within 1% of shortest are effective in congestion mitigation.

Framework supports safe and efficient pedestrian movement during COVID-19.

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 roadsand 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%