Shifting Paradigm the impact of Covid-19 on transport planning
The Neighborhood Idea A sound area for living with: 1. Adequate school and parks within a half mile walk 2. Major streets around rather than through the neighborhood 3. Separate residential and non residential districts 4. Population large enough to support an elementary school. Usually 5,000 to 10,000 people 5. Some neighborhood stores and service Reproduced from Comprehensive Planning for The Whittier Neighborhood, courtesy of Minneapolis City Planning Commission Reference: American Society of Planning Officials (1961). Neighborhood Boundaries. Information Report No. 141. Available at: https://www.planning.org/pas/reports/report141.htm.
Shifting Paradigm: the impact of Covid-19 on transport planning Shifting Paradigm: the impact of Covid-19 on transport planning, 1st Edition Made in Milan by Transform Transport © 2021 Systematica Srl All mobility studies presented in this book are developed by Transform Transport. All rights reserved. Unauthorised use is prohibited. No part of this publication may be reproduced in any form or by any means without the written permission of Systematica Srl. Systematica Srl Via Lovanio 8 20121 Milan, Italy +39 02 62 31 19 1 www.systematica.net email@example.com
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Table of Contents
Shifting Paradigm p.4 Walkable Streets p.6 ● milan sidewalks map ● milan sidewalks network
Living Local p.14 ● mapping milan microcenters ● access to green areas and public realm ● walkabilty and the 15-minute city model
Urban Metrics p.22 ● looking with machine eyes ● monitoring (big) traffic data through wi-fi sensors
Pedestrian Dynamics Simulation p.28 ● how covid-19 is affecting pedestrian modelling
Way Forward p.30
This booklet is a structured collection of the most insightful investigations developed by Transform Transport, the research unit of Systematica, since the Covid-19 outbreak. The unprecedented disruption caused by the pandemic has given rise to a large cultural and technical debate on upcoming new forms of urban development and mobility in an attempt to envision potential trajectories of new paradigms and keep up with the pace of our changing cities. Among all the possible urban challenges, walkability, universal accessibility, the public realm and living locally were recognized as crucial planning dimensions to tackle through a full-fledged approach. In particular, the recent focus on the ’15-minute citys’ paradigm represents a new perspective for evaluating sustainable, inclusive and resilient urban organisms, an inspiring point of contact between urban and mobility planning. The area of investigation, 4
actual analytical test bed of this booklet, is Milan, which reacted promptly to Covid-19 through the implementation of its adaptation plan. Through innovative city reading instruments, multi-dimensional urban metrics and deep learning techniques, this publication explores the dense network of sidewalks as well as the actual accessibility to urban parks, other key components of the public realm and essential services; it investigates hidden people movement patterns through big data and video/ image analytics, with the aim of arguing an emerging correlation that has identified, in the semi-central neighbourhoods of Milan, the most urgent urban issues to address. Calibrated on the city of Milan, this metric can be replicated in all global cities, with the aim of mapping urban structural gaps and inform effective intervention strategies. 5
Milan sidewalks map Walkable Streets Overcrowding and population density are by definition two crucial factors in the subject of pandemic risk. In a hyper-connected global world, inhabited by 7.5 billion people, 55% of whom are concentrated in urban areas (70% in 2050), emergency health risk situations are growing at an increasingly high rate. Social distancing is the most effective measure to prevent and contain the spread of pandemics. The restrictions we are experiencing today may therefore become a continuous part of our lives and the way we inhabit and plan our cities in the future. Social distancing and sidewalks In Lombardy, the recommended interpersonal distance for contagion containment is 1 meter. Starting from this assumption, we considered the space occupied by each person (0.6 m + 0.2 m of comfort zone), applied the 1 meter spacing and assumed different sidewalk sections. In this way, we defined intervals to evaluate the level of suitability of sidewalks based on their width. It should also be noted that the measurements referred to at this stage imply the net walkable width of the pavement.
Corso Buenos Aires in Milan
9,000/HR DEDICATED TRANSIT LANES
4,000-8,000/ HR TWO- WAY PROTECTED BIKEWAY
MIXED TRAFFIC WITH FREQUENT BUSES
1,000 - 2,800/HR
Mapping pedestrian infrastructure
Sidewalks in Milan
Pedestrian traffic is the primary and most capable "mode of transport". The study aims to highlight how the mapping of pedestrian infrastructure, here in particular of sidewalks, is fundamental and how much this is missing among the tools of administrations and planners. This tool would exponentially increase the ability to analyze and plan pedestrian spaces, serving fundamentally the need for rapid adaptation, which we are working towards and in line with the principles of sustainable mobility that many cities are promoting. The width of a sidewalk contributes to the level of comfort in using that infrastructure. Sidewalks that are too narrow can create zones of conflict where pedestrians encroach on road space, leading to dangerous situations. Comfortable sidewalks instead support and encourage pedestrian traffic by increasing the attractiveness of the street and bringing widespread advantages.
By analysing the data from the East of Milan, we developed a clear idea of the existing situation of the sidewalks. Particular attention should be paid to the sidewalks in the "ideal situation" category as part of them are actually occupied by trees, cycle lanes or by parked vehicles. On the other hand, 45% of the sidewalks do not meet the minimum requirements to guarantee adequate social distancing. In this sense, some measures that could be implemented to expand the space available on the sidewalks need to be taken into account: • Remove on-street parking and parked cars on sidewalks • Close, if even temporarily, a traffic lane Below is shown a set of maps for each category of sidewalk width. This would help looking at clusters and identify areas where to intervene first.
Sidewalks in Milan: Walkability is as important as ever in the Covid-19 moment
Urban furniture The resulting map depicts the gross width of the sidewalk from edge to edge, i.e. from the edge of the building to the roadway. What is not currently taken into consideration is the space occupied by street furniture: trees, lighting, benches, outdoor areas for commercial activities, etc. It is therefore reasonable to assume that the percentages shown in the previous pages are very conservative and a further detailing (through desk and on-site surveys) of the map is required. After a preliminary study, based on the sample analysis of a limited number of Milanese streets, we have reason to think that on average, on a neighbourhood street, about 0.3-0.5 m and 1.5-2 m of the gross width of the pavements (in the case of non-tree-lined streets and tree-lined streets, respectively) is occupied by street furniture. This analysis is purely indicative and confirms the need for a more systematic and detailed mapping of our pedestrian infrastructure. The goal is to further refine this work in order to define an approximate estimation of the size of street furniture to calculate the real available width of the sidewalk. Parking on sidewalks Unfortunately part of the sidewalks that are sufficiently wide for social distancing are physically occupied by parked cars. Parking on sidewalks reduces the attractiveness and comfort level for pedestrian users, while also contributing to a reduced level of safety. Undeniably, further studies looking at the distribution of these obstructive elements would provide deeper insights and allow for a more precise mapping of the real active widths of the pavements. 8
Milan sidewalks map: www.milansidewalks.com Sidewalks are valuable infrastructure that support everyday life in Milan. This map shows their width and critical areas where phisical distancing cannot be respected.
Today, Milan's pedestrian infrastructure does not guarantee a homogeneous level of security, with respect to current social distancing requirements necessary for the pandemic containment. It will therefore be necessary to encourage the implementation of wide-scale pedestrianization measures in several areas across the city, if even temporarily, in order to ensure safe pedestrian movement. It is of fundamental importance to have access to a comprehensive mapping of our city's pedestrian infrastructure. Undoubtedly, further detailing of the map is required to ensure reliability and up-todateness. It is also important to collaborate with city administrations to enable constant upgrading of the database. This mapping tool will be essential for cities in decision-making processes as a means to facilitate the identification of intervention clusters, define priority areas and design adaptation measures most effectively.
Journal and Conference Links: Deponte, D., Fossa, G., Gorrini, A. (2020). Shaping space for ever-changing mobility. Covid-19 lesson learned from Milan and its region. TeMA - Journal of Land Use, Mobility and Environment, 133-149. doi: 10.6092/1970-9870/6857 Abdelfattah, L., Bazzoni, F., Choubassi, C., Gorrini, A., Presicce, D., Zuretti, M. (2020). Sizing up post-pandemic sidewalk potential: A case study from Milan. In: Proceedings of the 56th ISOCARP World Planning Congress 2020, November 2020 February 2021 European Platform on Sustainable Urban Mobility Plans (2020). COVID-19 SUMP Practitioner Briefing. CIVITAS SATELLITE CSA. Website Link: https://research.systematica.net/research/milansidewalks-map/
Milan sidewalks network Walkable Streets This article proposes a useful methodology for identifying the most at-risk areas of the city, where interventions to adapt the pedestrian infrastructure must become a priority. The factors considered to determine the risk level of a specific area are undoubtedly multi-faceted. The methodology proposed in this study is intentionally simplified in order to identify more clearly the groups of users to whom we ought to focus our attention in a pandemic phase. More complex factors can undoubtedly be part of further developments of the methodology and are worth more in-depth studies.
Identification of key districts Narrow sidewalks / Focal point elderly population
Of all the elements that contribute to determining the level of risk for a given area, two main factors were considered in this study: 1. Elderly population: the density of the elderly population over the age of 70. This is in fact the slice of the population most at risk: 89% of the patients who died and were positive for COVID-19 fell under the age group of Over 70 (Source: the National Institute of Health - Istituto Superiore della Sanità). 2. Daily population: this figure indicates the daily active population for the different areas in terms of residents who stay at home, students and employees who travel to the workplace. This information essentially identifies the densest and most crowded areas during the day.
Narrow sidewalks with Priority 1 (elderly and dense) 169 km Narrow sidewalks with Priority 2 (elderly areas) 376 km Narrow sidewalks with Priority 3 (dense areas) 100 km Narrow sidewalks with no Priority 729 km Remaining sidewalks 1679 km Total sidewalks 3053 km
Priority of interventions By overlapping very dense areas, a map of the intervention priorities was obtained for those pavements classified as unsuitable. Three priority levels are thereby identified: Priority 1: pavements located in very dense areas where there is a high number of both the elderly and daily populations. Among these areas, the districts between the first and second ring roads stand out, such as Loreto, Porta Venezia, XXII Marzo, Porta Romana, Porta Genova, Sarpi. Priority 2: sidewalks in areas where there is a high density of older populations than the city average. These include some historic and mainly residential neighborhoodssuch as: Gallaratese, Villapizzone, Musocco, Niguarda / Affori, Maciachini, Lodi, Gratosoglio, Chiesa Rossa, Giambellino and Bande Nere. Priority 3: sidewalks in areas where there is a high presence of daily populations. Among these areas, areas that are particularly active during the day stand out, such as: Duomo, Città Studi and Porta Nuova.
Street in the City of Milan near Duomo (dense area)
Website Link: https://research.systematica.net/journal/milansidewalk-network/
Mapping Milan micro-centers Living Local Proximity, density and diversity: Local centers to support living at neighborhood-scale The Covid-19 pandemic has dramatically influenced the way we live and move. Movement within the city has been dramatically reduced in both the number of trips and duration of movement with preference for the private automobile, rather than public transport. As a result, the neighbourhood scale has returned to being extremely important; ensuring density, proximity and diversity of services in a widespread manner within the city is beneficial in order to reduce the pressure on local public transport, while at the same time, granting accessibility to all those necessary functions that we need in our daily lives. This is a key topic, and was being addressed prior to the pandemic as a concept known as the ‘15-minute City’. The ‘15-minute City’ is a term given to the vision adopted by the Mayor of Paris, Anne Hidalgo, whereby every resident is envisioned to be able to reach a number of essential services on foot or by bicycle within 15 minutes from their home. This concept rests on the idea of localized living, whereby residents could satisfy the bulk of their daily needs without the need for long motorized journeys. Neighborhood essential services For this concept to materialize, city administrations must assume a proactive role in defining the array of ‘essential services’ to define local micro-centers. The requirement to guarantee the diversity was to verify, within the predefined pedestrian area, the presence of at least one service for each macro-categories (food, health, open spaces, sports, education, work, culture/ leisure and mobility) considered. Starting from these identified local centers, the city was then mapped using the Voronoi tessellation method.
De-constructing the city identifying its local centers A mapping of the city using the Voronoi method can allow us to read the city as a tapestry of urban local centers of various access levels. All polygons indicated in pink have a dimension that allows to get access to all service categories in less than 15 minutes on foot; those in orange in 15 minutes by bike; and light blue areas are those in which the identified local centers cannot be reached by either mode in the given timeframe. A quick reading of the mapping result shows a clear transitory pattern from inner city districts, where local centers are denser and therefore more accessible by foot, to peripheral areas, where there are few centralities and it takes longer than 15 minutes to reach these areas. These neighborhoods offer a model for local living that should be studied to gain insights into plausible approaches to be adopted at city scale.
Local centers composition
If we look in more detail at data collected, we discover that an average pedestrian friendly micro-center (15 min walking area) in Milan is mainly composed of 330 shops (50% of the total), 170 bars/restaurants and 90 supermarkets (representing 40% of total services). This result should be used as basis for further reprogramming of service distribution.
For each category of urban micro-centers a set of strategic actions would be proposed to help bring each area type to its highest accessibility potential. Most of the areas in need, i.e. those which are not accessible either by foot or bicycle within 15 minutes require the most intensive intervention in the form of diversification and densification of services. Furthermore, in areas with sufficient foot accessibility, it is deemed suitable to improve pedestrian and cycling infrastructure to ensure easy and comfortable access to already existing services.
Journal and Conference Links: Abdelfattah, L., Bazzoni, F., Choubassi, C., Gorrini, A., Presicce, D., Zuretti, M. (2020). Exposing unbalanced service distribution in urban areas: The case of Milan. In: Proceedings of the 56th ISOCARP World Planning Congress 2020, November 2020 - February 2021 (online) Website Link: https://research.systematica.net/journal/livinglocal-mapping-milan-micro-centers/
Access to green areas and public realm Living Local The pandemic is affecting change in consolidated social behaviors, which resonates particularly in urban areas. Indeed, it is precisely in such realities that the community can rediscover the importance of access to open-air gathering spaces and perceive, in many circumstances, the lack of easily accessible public spaces on foot from home. The study originates from a comprehensive survey of Milan’s public space. Data collected from official sources and platforms are integrated with ad-hoc researches to create an atlas of the main categories of public spaces such as parks, gardens, dog areas, oratories, plazas and pedestrian areas. The overall extent of Milan’s public realm reaches 21.000.000 sqm. Parks and gardens are predominant, occupying 11% of the municipal area.
Parco Biblioteca degli Alberi in Milan
15-minute accessibility to urban parks
Playgrounds Dog area
Ped. Medium Parks Oratori area
Public realm categories, size and distribution
The isochronal analysis allows identifying urban areas whose residents live less than 15 minutes away on foot from a specific point. This reading of the city brings out the number of inhabitants able to reach a recreational area in less than 15 minutes and the urban areas least served. Investigations show that the distribution of medium and large public parks leaves some areas of the city uncovered. The diffusion of other recreational areas reduces this deficiency by ensuring a widespread coverage of the city. Nonetheless, the supply of these areas is reduced, resulting in 1.4 sqm per capita, on average. The map shows the detailed processing of the results obtained through the isochronal analysis. The analytical process starts with the public space provision within 15 minutes from each census cell.
Gathering area provision (m²)
Non residential areas Gathering areas
Then, information about the residing population is analyzed. The methodology allows us to obtain a synthesized reading of the municipal area that compares the population density with the availability of recreational areas within 15 minutes from each census cell. The chromatic scale identifies the total amount of recreational areas available to each resident within 15 minutes. As shown on the map, more critical zones are located in proximity to the external ring-road, with episodic extensions along the north-east, south-east and west axial roads.
653,000 Inhabitants of scarely served areas 293,000 Inhabitants of medium served areas 294,000 Inhabitants of highly served areas roads potentially closed to vehicle traffic are reported in red. This strategy can be implemented temporarily during the pandemic spread or occasionally during weekends to ensure the enhanced provision of secure public spaces where needed. Some of these transformations can hopefully become permanent in order to give a balanced accessibility to public realm to residents.
Seeking an equilibrium The conclusion of the study intends to provide preliminary guidelines for a homogenization of the public realm across the municipal territory with the ambition to contribute to the development of a structured and suitable response to the social developments underway. Finally, a selection of actions taken on the global scale to expand existing public realm are considered. Among the proposed interventions aimed at increasing public space, the capillary local roads network, green in the map, can play a crucial role. The quota of local
Website Link: https://research.systematica.net/research/ access-to-green-areas-and-public-realm-thecase-of-milan/
Walkability and the 15-minute city model Living Local A two-pronged approach for the City of Milan
A demand-driven approach to chrono-centric cities
The 15-minute city idea is founded on a radical approach to urban planning that revaluates the neighbourhood scale and assesses accessibility to essential services on the basis of walking and cycling. It is essentially a rights-based model promoting hyper-proximity as a vision for an equitable, viable and liveable urban system. In the following analysis, we utilize the chrono-centric ‘15-minute’ framework to evaluate the spatial distribution of walkable neighbourhoods across Milan, identifying areas in need of intervention using a population-based analysis.
Experimenting with chrono-centric heat maps of the city of Milan, we obtain a population-driven narrative of the walkable city, i.e. a map highlighting the places accessible to the highest portion of the population within a 15-minute walk. We compare cumulative and working population density: the highest concentration of the resident population are within reasonable walking distance to the districts of the second ring road area, whereas the distribution of the working population (i.e. employees at places of work) cluster strongly in central districts.
Access to at least 7 categories of services
5 minutes 10 minutes 15 minutes Not accessible in 15 minutes
Walkscore (15 minutes)
Population Working Population
On the other hand, if we look at the supply side of the equation, i.e. the walkability of the pedestrian network and the distribution of services, we find that these results do not completely match the highest demand areas. Some pockets of high demand lack the accessibility to seven basic service categories of a total of nine, which are: food, culture, education, commercial (non-food), parks, restaurants, health, sports, other (such as banks, post office, etc.). A walkability analysis using Walk Score© also confirms these findings. Set at a 15-minute radius, the analysis reveals some lower scoring areas in the north of Milan that despite good service access, are not highly walkable. A closer look at walkability values in relation to population demand emphasizes this mismatch. The above chart highlights a striking correlation between nearness of a district to the city center and high walkability levels. On the other hand, no clear trend can be established between population distribution and walkability or closeness to the centre. In fact, many neighborhoods with high population access have low walkability scores. These neighborhoods have high attraction potential but low pedestrian accessibility to services, signifying a need for intervention to promote equal access to services on foot across the city. Intermodal support for the interim phase Micro-mobility services and on-demand transit can help alleviate the burdens of a low walkable environment in the short run. Currently, only half of Milan benefits from the ease and convenience of a 15-minute city. A practical solution to support the model could be to boost first-and-last-mile mobility solutions to extend accessibility ranges while maintaining limited trip times and energy costs.
Global trends show that micro-mobility devices have a significant role in reducing the first-and-last-mile gap and are often paired with public transport. One of the main limitations of micro-mobility, however, is its demographic exclusion of higher age groups. For older citizens and users with assisted mobility needs, ondemand transport may be a more suitable intermodal solution. Zero-minute trips and reflections for a hybrid 15-minute model A critical understanding of mobility, which considers digital as well as physical infrastructure is essential for accurately representing the 15-minute city. ‘Zerominute trips’ should be introduced as part of a new hybrid conception of the 15-minute city that considers the contributions of digital infrastructures in replacing physical trips. Examples of ‘zero-minute trips’ include work trips (due to the acceleration in remote working arrangements) and public service trips (due to developments in e-government services). Both of these categories have been largely augmented by the pandemic situation. Such synergies can have major implications for urban mobility markets worldwide; making the challenge to promote chronologically balanced cities significantly easier.
Journal and Conference Links: Abdelfattah, L., Deponte, D., & Fossa, G. (2021). 15-Minute City: Interpreting The Model To Bring Out Urban Resiliencies. In: Proceedings for the XXV International Conference on Living and Walking in Cities (submitted).
Looking with machine eyes Urban Metrics How deep learning helps us reading our cities The development of new technologies is shaping the growth of cities in many ways. As recently highlighted by the European Commission (2020), the Internet of Things (IoT), Artificial Intelligence (AI), the highresolution global positioning system (GPS), big data and new building materials and techniques are expected to transform cities’ core functioning elements, affecting all aspects of our lives. When technology is combined with the growing availability of open data, new possibilities emerge to develop a novel understanding of the urban fabric and use. Enabling data and methodology Deep learning algorithms are a subset of machine learning algorithms, which process and combine their input in ever growing abstractions to obtain meaningful outputs. These are of particular interest in the field of computer vision, enabling the manipulation of large datasets in an automatic way. In the past years, the rising availability of deep learning techniques lead to new frontiers in the automatic understanding of images and estimating the number of objects within an People manual
image. In particular, deep learning methods obtained state-of-the-art results for image classification, object detection and instance/semantic segmentation tasks. Furthermore, in the past years, the availability of pretrained weights for deep learning algorithms has grown. This project focuses on the analysis of pre-trained deep learning models for object detection (i.e. YOLOv3, Faster R-CNN), image segmentation (i.e. Mask R-CNN) and crowd counting (i.e. CSRNet). The first two aim to recognize objects and locate them in an image, outputting their bounding boxes or shape masks; the latter aims to estimate the number of people. The initial purpose was to assess their flaws and potentials given a dataset of images of Corso Buenos Aires, a well-known shopping street in Milano. First, a subset of images was selected, these represent different moments of the year and are used as a means of assessment for the performance of the models. The second goal was to investigate the use of the street for a year period. Thus, the best performing algorithms were used to perform an analysis of the use of the street from September 2019 until September 2020, with a focus on the Covid-19 pandemic lockdown period.
People Faster R-CNN
The graph summarizes how different methods performed on the pedestrian detection task, compared to manual counts on eight test days with different congestion and light conditions.
People Mask R-CNN
The graph shows the comparison between the number of pedestrians computed with the object detection algorithm Mask R-CNN and the crowd counting algorithm CSRNet between September 2019 and September 2020.
Conclusions and future research The results obtained provide valuable insights for future analyses using object detection and image segmentation methods. Firstly, the position and orientation of the camera can influence the outputs greatly. Images that present a high perspective view are not best suited for detection tasks, where instances of the same class should have a similar dimension throughout the frame and should be visible with little occlusions. Secondly, the use of pre-trained models without modifications give satisfying results for the images of Corso Buenos Aires only for a reduced portion of the original picture and for bigger instances, such as cars. Modifying the anchors’ sizes could improve the results for smaller objects, however it would not be sufficient to recognize parked bicycles and motorcycles, which are very close to each other. The research also highlighted a range of potential
applications for object detection and image segmentation methods. A first example is an analysis on how differential speed limits and the consequent interaction between different types of vehicles within a street can affect safety. Furthermore, images and videos could be used to track movement patterns of a person or groups of people and understand their behaviour in different context. Behavioural analysis can also be linked to climate-driven route choices, for example, a study of the use of Corso Buenos Aires sidewalks based on the sunlight’s angle.
Website Link: https://research.systematica.net/journal/lookingwith-machine-eyes-how-deep-learning-helps-usread-our-cities/
Monitoring (Big) traffic data through Wi-Fi sensors Urban Metrics The management and optimization of transport infrastructure requires the monitoring of (Big) traffic data in real time in order to assess the contextual conditions of service, detect anomalies and avoid service disruption. Nowadays, monitoring traffic data has become even more crucial considering the need to investigate the unprecedented effects of the Covid-19 pandemic on urban mobility and to assess the effectiveness of immediate and longer-term actions that cities are developing to respond to the crisis. In this regard, the activity of transport planners and decision makers is supported by the development of ICT solutions for monitoring, understanding and predicting the travel behaviour of the city users through location detection systems, including the following: images or video stream analysis-acquisition systems; radio frequency systems based on Wi-Fi or Bluetooth wireless technology; cell network data acquisition systems; software development kit, Beacon and bidstream systems; occupancy Detection Systems.
The map shows the results of a 7-months period of data collection (from January 1st, 2020, to July 31st, 2020), which consists of about 114 million of mobile devices counted in total.
The Evolution of the Lockdown Phases in Milan Thanks to the collaboration with the Wi-Fi service provider FreeLuna, Systematica analysed the (Big) traffic data collected in Milan through a network of WiFi sensors from the beginning of January 2020 to the end of July 2020. The aggregated dataset includes vehicular, cycling and pedestrian flows. In general, the analysis was based on filtering the number of mobile devices (e.g., smartphones, tablets, notebooks, etc.) counted per hour by means of a total of 55 Wi-Fi Access Points, distributed in several department stores, shops and public services.
The chart shows the results of the time series analysis of traffic data collected through Wi-Fi sensors during the Pre-Covid-19 period (from January 1st, 2020, to February 22nd, 2020) and the lockdown phases.
The Circadian Rhythm of Milan Before and After the COVID-19 Pandemic Data analysis focused on the average weekly distribution of the number of mobile devices counted through the Wi-Fi sensors during the Pre-Covid-19 period (from January 1st, 2020, to February 22nd, 2020) and during the period between Phase 0 and Phase 3 (from February 23rd, 2020, to July 31st, 2020, -64% compared to the Pre-Covid-19 period). The relative quintile frequency distribution of results allowed the characterization of the circadian rhythm of the City of Milan during the entire time series of data. Delta Values and Location-based Data about POIs An extensive GIS-based spatial analysis was executed to calculate the density distribution of the Points of Interest (POIs) located within the catchment area of each Wi-Fi Access Point: bank and ATM (6%), bar, cafè, pub and nightclub (18%), cinema and theatre (1%), department store (1%), fast food and restaurant (25%), health service (4%), place of worship (0.4%), public service (3%), shop (30%), supermarket (1%), tourists attraction (9%). The results of the analysis showed that the traffic flows observed during the Pre-Covid-19 period were concentrated in the Milan city center, as the area characterized by the highest density distribution of POIs. Moreover, results showed that the centrality of POIs was also linked to the lower variance of traffic flows observed during Phases 0-3 in peripheral areas. This opens up debate on the need to design cities to have a polycentric structure, with several and distinctive areas of attraction for the city users, in order to be resilient to extraordinary events such as the Covid-19 pandemic. Final Remarks and Future Work The results of the proposed research work could be of notable interest for those interested in data-driven approaches for transport planning. Future work will be based on the use of computer vision techniques to cross check the validity of traffic data collected through the Wi-Fi sensors, and on the development of Wi-Fi sensing applications for monitoring mobility data in real time considering both outdoor and indoor scenarios.
Journal and Conference Links: Gorrini, A., Messa, F., Ceccarelli, G., Choubassi, R. (2020). Covid-19 pandemic and urban mobility in Milan. Wi-Fi sensors and location-based data. TeMA - Journal of Land Use, Mobility and Environment (in press) Website Link: https://research.systematica.net/journal/howcovid-19-is-affecting-pedestrian-modelling/ In collaboration with FreeLuna.
How Covid-19 is affecting pedestrian modelling Pedestrian Dynamics Simulation Computer-based systems for the simulation of pedestrian dynamics provide optimized solutions for supporting the activity of transport planners and decision makers in the design of transport infrastructures. This is based on the possibility to evaluate key performance indicators (e.g., travel time, density condition, waiting time), to test the efficiency, comfort and safety of alternative spatial layouts and traffic management conditions (i.e. what-if scenarios) in a predictive and explanatory scheme. Static assessment metrics already allowed to define the negative effects of disruption related to COVID-19 pandemic crisis on mass transit/ gathering infrastructure capacity. The current work is aimed at applying simulation models to investigate the phenomenon in dynamic conditions focusing on pedestrian mobility. In particular, we applied a descriptive set of metrics and parameters for representing the impact of social distancing into the Social Force Model of the pedestrian simulation platform PTV Viswalk. We focused on calibrating the dynamic regulation of interpersonal distances among pedestrians (i.e. social isotropic parameters related to repulsive force), to avoid conditions of inappropriate proximity and spatial restriction due to high density situations. The proposed calibration phase allowed us to compare simulation results between the Social Force Model and the proposed Social Distancing Model. Results showed that (i) pedestrian dynamics driven by the Social Force model (ordinary conditions) were characterized by temporary/local situations of high density and queueing due to the limited capability of the infrastructure to accommodate pedestrian flows, and that (ii) pedestrian dynamics driven by the Social Distancing Model (tested condition) were characterized by continuous detouring maneuvers and speed adjustment to avoid proximity with other agents. 28
Simulation results achieved through the Social Force Model and the proposed Social Distancing Model.
The proposed approach an innovative contribution for the estimation of the impact of social distancing on pedestrian dynamics, comparing the traditional approaches devoted to the mere estimation of flow rate and Level of Service. This is linked to the possibility to evaluate the need to provide short-term urban mobility and transport planning interventions (e.g. temporary enlargement of sidewalk infrastructures, queue management in transit infrastructure), within an-evidence based approach. Given the current level of maturity and expressiveness of commercial simulation platforms in modeling social distancing dynamics among pedestrian flows, the proposed approach represents a preliminary test based on an experimental calibration phase. The calibrated microscopic model was used as a basis to build the fundamental diagrams of pedestrian flow under social distancing conditions. By changing the input demand and analyzing the variation of both the mean speed and density, three main macroscopic parameters were identified: Capacity [ped/min/m], Free-flow Speed [m/s] and Volume-Delay Function. These properties were used to approach the social distancing route choice problem in a large scale through a macroscopic model.
The case of study was Venice, a city certainly unique in the world. Most trips in the Venetian Lagoon are made by walking or by a combination of water travel and walking. The pedestrian network in the Main Island is quite complex for non-familiar users, limiting the route choice efficiency. In addition, many routes connecting the main attraction and generation points in the island converge into narrow streets, where social distancing is not guaranteed during peak hours. These conditions make of Venice an interesting case to apply the proposed approach. The model extension is the main island of the Venetian Lagoon. The pedestrian OD matrix takes into account both external trips (between the island and the dry land) and internal trips (Origin and Destination within the island). External trips were extracted from the city-scale multimodal strategic transport model of Venice, accounting for the specific mode in which people enter or exit the island (car, bus, tram or rail). This allowed to identify the access or egress point of the internal network where each pedestrian path leg starts or ends (Piazzale Roma Terminus, Tronchetto P&R Facility or Santa Lucia Railway Station). For both internal and external trips, the modal split within the island is estimated (walking vs. navigation) prior to the pedestrian assignment in the subarea model.
Internal trips desire lines
The pedestrian assignment with the social distancing model (SDM) was compared with the BAU assignment (Business As Usual). The SDM assignment finds a new equilibrium in the network by redistributing pedestrian flows into a wider range of routes, reducing the pedestrian density. The map below shows flows increase (red) and reduction (green) in the SDM assignment compared to the BAU.
Flow Reduction Flow Increase
Pedestrian Assignment Comparison (SDM vs. BAU)
The SDM assignment showed an increase of more than 40% in the number of routes used in the equilibrium assignment, and an increase of 10% in the length of used network, while the average travel time increased by only 6%. These kind of models represent an opportunity to implement smart and dynamic wayfinding systems in pedestrian networks with high demand concentration in specific generation and attraction points, taking into account not only distance and travel time under normal conditions, but also social distancing when necessary.
Journal and Conference Links: Deponte, D., Fossa, G., Gorrini, A. (2020). Shaping space for ever-changing mobility. Covid-19 lesson learned from Milan and its region. TeMA - Journal of Land Use, Mobility and Environment, 133-149. doi: 10.6092/1970-9870/6857 Espitia, E., Vacca, A., Gorrini, A., Deponte, D., Sarvi, M. (Ongoing). How Covid-19 is Affecting Pedestrian Modelling and Simulation: The Case of Venice. To be submitted to: Transportation Research Board 101st Annual Meeting - TRB 2022, 9-13 January 2022, Washington DC, USA. Website Link: https://research.systematica.net/journal/howcovid-19-is-affecting-pedestrian-modelling/ In collaboration with PTV Group.
Total desire lines
Way Forward Covid-19 has triggered a series of theoretical reflections and urban experiments, whether through research or physical urban interventions, which we, at Transform Transport, could not but be part of. We have witnessed these changes steered by the need to adapt to the new conditions that the pandemic imposed on us. We kicked off our research days after the outbreak of the pandemic and, today more than a year later, our efforts are relentless and our aim is to bring this urban research endeavour to a second level, which does not only look into the here-and-now, but also sheds light on how we plan our future cities. The pandemic pushed cities worldwide to change the way planners read cities, giving value to some assets more than others, such as the walkable networks, alternative modes of transportation, the benefits of changing working habits, and 30
the immense capability of open space and the public realm in giving value to our daily lives and cities in general. The experiments and studies presented in this booklet will turn into a living legacy while planning out future cities, as we continuously introduce new parameters for measuring effectiveness and setting priorities. These studies will be further developed and consolidated to shift from being a simple analytical framework into a set of robust design principles that would steer the process of planning and city making. This is hinged on a profound understanding of our changing habits and the degree to which our cities need to adapt fast to abrupt changes. Our contribution to better cities through research might seem minimal however we firmly believe that developing new methods for reading the status quo will increase awareness and the sensitivity of our planning tools, thus paving the way for a gradual and everlasting change to the practice of urban and transportation planning. 31
Systematica Srl Established in 1989, Systematica is a transportation planning and mobility engineering consultancy with its main office in Milan, Italy and subsidiary offices in Beirut, Mumbai, and New York City. Systematica provides a wide array of integrated consultancy services in the sectors of transportation and urban planning and operates at multiple scales with expertise at the national, regional, and urban development scale of transportation planning. Systematica provides strategic advisory and due diligence for infrastructure investments, traffic analysis and management, and mobility engineering in complex buildings and event venues. In addition, specialization in pedestrian flows, parking design, and vertical transportation are provided as a core service. As technology is rapidly changing the transportation planning realm, Systematica is actively engaged in the research and application of advanced information mobility systems and technologies. Systematica has three-decades of experience in providing quality service to clients, international experience in complex environments, and expertise in the usage of sophisticated analytical mapping instruments and traffic modeling software. Its widely acknowledged tailor-made approach has made it possible for Systematica to work on complex projects around the globe in equally diverse contexts. The evidence-based approach of Systematica is underpinned and supported by an extensive use of transportation modeling tools and simulation platforms aimed to explore and identify the most suitable planning solutions in every context and at any scale. www.systematica.net
Transform Transport Transform Transport is Systematica's research unit focused on innovative mobility solutions. While mobility and transport related technologies are emerging with increasingly fast paced, Transform Transport explores how they can have positive impacts on our cities, neighborhood and buildings. Founded by Systematica, it grounds on 30 years of experience in the field of transport planning and mobility engineering, investigating the future of Milan and other cities worldwide. research.systematica.net
Credits Shifting Paradigm: the impact of Covid-19 on transport planning, 1st Edition Team: Lamia Abdelfattah, Filippo Bazzoni, Giulia Boni, Oxana Borovkova, Simone Castelnuovo, Giulia Ceccarelli, Ana Gaby Chavez, Rawad Choubassi, Diego Deponte, Eduardo Espitia, Andrea Gorrini, Jonelle Hanson, Matteo Marconi, Federico Messa, Dante Presicce, Caroline Purps, Nicola Ratti, Alessandro Vacca, Marianna Zuretti. A special thanks to all collaborators of Systematica who contributed to this book.