Applying a Pedestrian Level of Service in the Context of Social Distancing: The Case of the City of Madrid

Abstract

During the COVID-19 pandemic, there has been a lot of discussion about keeping interpersonal distance to prevent the virus from spreading. To keep this interpersonal distance, authorities at different levels have taken measures to reduce people’s interactions, such as reducing capacities, curfews, pop-up cycle lanes, temporary pedestrianisation, and lockdowns. Many of these temporary measures have been perceived from a static view. Nevertheless, in a scenario of “new normality” or in the face of a possible new pandemic, the amount of data (big data) generated by different sources, such as sensors, in large cities has extraordinary potential to be used together with tactical urbanism for quick adaptation. The aim of this study was to gain insight into the aforementioned issues by analysing spatio-temporal patterns of pedestrian mobility and developing a variation of the pedestrian level of service measure; the pandemic pedestrian level of service (P-PLOS). This measure provides a dynamic view of pavement capacities according to the interpersonal distance recommendations during the pandemic. P-PLOS was tested in the city of Madrid based on the pedestrian counter data that was provided by the local government through its open data website. We found that the application of P-PLOS, together with street design, allows for knowing where and when it is necessary to take tactical urbanism measures in order to maintain or improve the level of service, as well as where it is necessary to take measures to reduce pedestrian flow.

On the path to develop a micromobility journey planner for Madrid: A tool to estimate, visualize, and analyze cycling and other shared mobility services’ flow

“…The delivered "shortest" (for moped) and "friendly" routes (for bikes and scooters) show that the journey planner works, although it is still in a beta version (under development). However, findings related to Madrid's dynamic show to be consistent with spatiotemporal travel patterns found in previous studies (Arias Romanillos, 2018Talavera-García & Pérez-Campaña, 2021).…”

Actas del XIX Congreso de Tecnologías de la Información Geográfica. TIG al servicio de los ODS Zaragoza, 12 a 14 de septiembre de 2022

“…Uncovering spatio-temporal micromobility patterns using the Time Geography framework 579 can be observed, supporting what was also found by (Romanillos et al 2018;Talavera-García and Pérez-Campaña 2021). In the previous figure we also show the percentage of times that each location (hexagon) is a hot spot (with p-value 0,05) which enables us to quickly identify the most important areas of the city regarding micromobility departures (origin points).…”

Evaluating the Impact of COVID-19 on the Behaviour of Pedestrians

“…Although PLOS models have been widely used in the literature, different studies have been conducted to improve the PLOS models based on different pedestrian needs. A Pandemic LOS has been developed using quantitative variables such as pedestrian space, walkway width, and speed to assess the PLOS during COVID-19 in the city of Madrid [17]. Nag et al (2020) [18] found that factors influencing pedestrian comfort can be categorised into three, including (1) flow characteristics of pedestrians and vehicular traffic, (2) physical elements of the built walking environment, and (3) users' perception of the walking environment.…”