This article investigates the phenomenon of transport poverty in the City of Milan (Italy), utilizing a comprehensive analysis of socio-demographic data in relation to the Public Transport Accessibility Level (PTAL) across the city. The study focuses on vulnerable populations, including unemployment, the elderly, and minorities, to identify the intersections between socio-economic disadvantages and public transport accessibility. By employing a bivariate index, the research delineates areas within Milan that exhibit both a high concentration of vulnerable residents and low accessibility to public transport services. The findings reveal significant disparities in transport access, highlighting specific neighborhoods where transport poverty is most acute. This analysis not only underscores the critical need for targeted transport policies to alleviate accessibility challenges faced by vulnerable groups but also contributes to the broader discourse on social equity in urban mobility.
Introduction
Transport Poverty is a globally widespread issue, it takes into account the overlapping consequences of two macro-categories of social and urban dynamics: accessibility to different modes of transport and socio-economic vulnerabilities. In the EU context, Transport Poverty has been brought up consistently in relation to policies aimed at obtaining a fair transition towards climate neutrality, as systemic challenges such as car dependence and insufficient public transport infrastructure disproportionately affect marginalized populations (Eurocities, 2024). Mattioli (2021) discusses how Transport Poverty in Europe is often linked to broader socio-economic issues, with many individuals relying on personal vehicles, thereby exacerbating the challenges faced by those without access to cars.
The European Commission’s report on Transport Poverty further underscores the necessity for targeted indicators and mitigation strategies to address these disparities effectively. By employing robust metrics and comprehensive analyses, policymakers can better understand the complexities of Transport Poverty and work towards creating more equitable public transport systems that cater to the needs of all citizens.
The Final Report on Transport Poverty (Cludius et al., 2024, p. 20) provides a working definition of Transport Poverty as “an individuals and households inability or difficulty to meet costs of private or public transport, or their lack of or limited access to transport needed for their access to essential socioeconomic services and activities, considering the national and spatial context”. This conceptualization covers the main core dimensions of availability, accessibility and affordability and the cross-cutting issues involving adequacy of transport, spatial dimension and socio-economic dimension (see Figure 1).

One prominent metric for evaluating the accessibility of local public transport is the Public Transport Accessibility Level (PTAL) (Transport for London, 2010), which quantifies how easily residents can access public transport services. Research indicates that improved PTAL scores correlate with enhanced operational efficiency in public transport systems, guiding urban development and alleviating issues such as traffic congestion and environmental pollution (Su, 2023).
Furthermore, studies have shown that significant portions of urban populations, particularly low-income groups, reside in areas characterized by low public transport supply despite high demand, highlighting the inequitable distribution of transport resources (Peungnumsai et al., 2020; Ajayi et al., 2022). This inequity is further exacerbated for vulnerable populations, who often face greater barriers to accessing public transport due to physical, economic, and social constraints (Kaszczyszyn & Sypion-Dutkowska, 2019).
To assess the level of vulnerability within populations regarding transport accessibility, various factors must be considered, such as income levels, age demographics, and immigration status (Nie et al., 2024). For instance, older adults and low-income individuals frequently encounter substantial challenges in accessing essential services, including healthcare and employment opportunities, due to inadequate public transport options (Syed et al., 2013). The development of specialized indices, such as the Elderly Public Transport Accessibility Index (EPTAI), has been proposed to specifically measure the accessibility of public transport for older travelers, taking into account their unique travel needs and patterns (Fatima et al., 2022).
Examples of analysis and representation of this issue are being developed on a city scale for case studies such as Munich, Tunis (Mobility (In)Justice Atlas, 2023) and Toronto (Transportation Equity Dashboard, 2024), with the development of interactive digital maps representing the various aspects involved in this complex phenomenon.
Enabling Data and Methodology
The methodology adopted in this research is predicated upon a systematic data collection framework designed to facilitate replicability across the national context. Initially, the investigation sought to identify and catalog available datasets pertinent to the study, with a particular emphasis on vulnerability factors derived from the National Institute of Statistics (ISTAT, 2021). This preliminary phase was critical in establishing a robust methodological foundation that could be uniformly applied in diverse geographical settings. Complementarily, the study incorporated General Transit Feed Specification (GTFS) (AMAT, 2024) data specific to the city of Milan, which served as a vital component for the calculation of the PTAL.
Subsequent to the acquisition of these datasets, both were spatially organized within a standardized hexagonal grid framework using the Uber’s Hexagonal Hierarchical Spatial Index (2018). This methodological choice enabled a coherent spatial intersection of the datasets, thereby facilitating a nuanced analysis of the relationship between public transit accessibility and vulnerability factors.
The vulnerability factors sourced from ISTAT were used to develop a composite index designed to identify areas exhibiting multiple aspects of social vulnerability. The index was constructed using six key indicators: (i) percentage of children (aged 0–14); (ii) percentage of elderly residents (aged 65+); (iii) percentage of women; (iv) percentage of non-EU citizens; (v) percentage of unemployed individuals; and (vi) percentage of individuals with low educational attainment.
These indicators, originally available at the census zone level, were first converted to the H3 Level 9 hexagonal grid and for each indicator, the proportion of the vulnerable population was calculated relative to the total population within each H3 cell. Then, each H3 Level 9 cell was ranked by percentile for each indicator, representing the relative presence of vulnerability factors. Finally, the overall vulnerability index for each cell was determined by calculating the average of these percentiles across all six indicators.
The PTAL method was used to measure accessibility to public transport and identify areas lacking sufficient service coverage. The index was calculated using the same spatial unit as the vulnerability index (H3 Level 9) to ensure comparability. Its calculation follows a structured process: first, the Point of Interest (POI) is defined, and walking access times from the POI to Service Access Points (SAPs) are determined. Then, valid routes at each SAP are identified, and their average wait times are calculated. For each route, the minimum total access time is computed and converted into Equivalent Doorstep Frequencies (EDFs), which allow for comparisons of service benefits at different distances. Finally, the EDFs are aggregated using a weighting factor that prioritizes the most dominant route for each mode. Based on the results, PTALs are categorized into six banded levels to reflect accessibility.
The vulnerability index and accessibility index were each divided into three tertiles, representing low, medium, and high levels. These were then spatially overlapped to identify the most vulnerable areas at the H3 cell level. The result of this process was the development of a bivariate index, which effectively visualizes the interplay between these two critical dimensions. This methodological approach not only enhances the understanding of transit accessibility but also aligns with contemporary academic discourse advocating for equitable public transport solutions (Guthrie et al., 2017). Additionally, the indices were averaged at the Nuclei di Identità Locale (NIL) level, Milan’s 88 administrative zones, to provide an aggregated measure of vulnerability across the city.
Results
The results give an overview of the spatial distribution in the city of Milan of the two main aspects concerning Transport Poverty, the distribution of accessibility to transport, specifically public transport (PTAL level), and the distribution of socio-economic vulnerabilities.
Public Transit Accessibility Level
The Public Transit Accessibility Level (PTAL) is an index designed to quantify the accessibility of public transportation services within a designated geographical area. This index assigns a score ranging from 0 to 6, with a score of 0 reflecting extremely limited access to public transport, while a score of 6 signifies outstanding access. The PTAL assessment incorporates various factors, including the frequency of service, the speed of transit options, and the distance to public transport facilities within the area (TfL, 2010). The results show a high access to public transport in the center of Milan which lowers towards the outskirts of the city (see Figure 2), the access is particularly low in the peripheral urban districts north-west of Milan (Certosa, San Siro and Bisceglie) and east (the external areas of Lambrate and Forlanini);

Vulnerability Index
The Vulnerability Index shows the spatial distribution of social vulnerability in the city of Milan. As previously stated, the Index represents the sum of six vulnerable indicators, visible on a scale ranging from low to high presence of vulnerability. The following images show the spatial distribution of the six individual categories of vulnerability, representing the proportion of the vulnerable population relatively to the total population within each H3 cell. The vulnerability indicators show a generally homogeneous spatial distribution (see Figure 3), apart from the presence of elderly population slightly more concentrated in the peripheral areas and the presence of women more concentrated in the center of the city. A figure that stands out is the spatial distribution of Low Education Attainment, which is very low in the central part of the city and markedly increases concentrically towards the outskirts.
Bivariate Map
The bivariate Accessibility-Vulnerability index shows the spatial distribution and intersection of the accessibility index and vulnerability index, determined by calculating the average of all the six previously viewed vulnerability indicators. The most problematic areas are the ones where the highest vulnerability level coincides with the lowest accessibility level, they can be recognized in the image as bright red (see Figure 4). These areas are located especially in the north-west section of the city of Milan, including the peripheral districts of Certosa, San Siro and Bisceglie; they are also visible in the south of the city, in areas such as Corvetto.

Among the most vulnerable urban districts, Nuclei di Identità Locale (NIL), i.e. those with high social vulnerability and low accessibility, those to the north-west of the city (e.g., Quarto Oggiaro – Vialba – Musocco, Figino, Quinto Romano, Baggio – Q.re degli Olmi – Q.re Valsesia, Assiano) and to the south (e.g., Barona, Ronchetto sul Naviglio, Chiaravalle and Parco delle Abbazie) stand out, see Figure 5.

Figure 5 Geographic distribution of areas with a high level of vulnerability and a low PTAL level in the city of Milan, divided by NILs (urban districts). The NILs that stand out are the following: Quarto Oggiaro – Vialba – Musocco (76), Bovisasca (81), Figino (63), Parco Bosco in città (88), Quinto Romano (62), Baggio – Q.re degli Olmi – Q.re Valsesia (55), Assiano (87), Barona (46), Ronchetto sul Naviglio (48), Chiaravalle and Parco delle Abbazie (85)
Conclusions and Future Works
This study provides a comprehensive analysis of transport poverty in Milan, shedding light on the critical intersections between socio-economic vulnerability and public transport accessibility. By employing a bivariate index to map areas of concern, the research identifies neighbourhoods where the confluence of high vulnerability and low transport accessibility is most pronounced. These findings are instrumental in guiding urban planning and policy decisions, with the downside that the use of GTFS data limits the methodology to locations which have that data availability, particularly big cities. In the case of Milan, however, it proves useful to determine a targeted implementation of new transportation services and the enhancement of existing ones.
The results offer actionable insights into where new public transportation services should be implemented to address the disparities identified. By prioritizing these areas, policymakers can help rebalance the urban mobility landscape, ensuring equitable access to public transport for all residents, particularly those who are most vulnerable. This targeted approach not only addresses immediate accessibility challenges but also contributes to fostering greater social equity within Milan’s urban framework.
Building on the insights gained from this study, future research will focus on replicating the proposed methodology at a national scale to develop a more comprehensive understanding of transport poverty. The objective is to be able to make an assessment on transport poverty not only within the context of big cities, but also in peri-urban areas that are often underserved by public transportation, by taking into consideration the different population density and land use.
To enhance the scalability and adaptability of the methodology, the Public Transport Opportunity Level (PTOL) index will be employed instead of the Public Transport Accessibility Level (PTAL). PTOL is a simplified version of PTAL, based on OpenStreetMap data about the location of public transport, not including GTFS data about the frequency of the service. The methodology involves the calculation of differentiated isochrones for the catchment areas of bus, tram and metro stations and railway stations. It will be used to assess the accessibility of public transport, identifying areas where the absence of transport infrastructure coincides with the presence of vulnerable population. This expanded scope will provide valuable insights into transport accessibility disparities nationwide and guide the development of inclusive, equitable transport policies on a national scale.
The results of this research have been presented at the International Conference Intermobility Future Ways, during the session “Più mobilità condivisa, meno povertà dei trasporti” (More Shared Mobility, Less Transport Poverty), held in Rimini (Italy) on the 19th of November 2024.
Acknowledgments
We are grateful to Fondazione per lo Sviluppo Sostenibile for their contribution to
the research. The data analyzed was treated in accordance with the General Data
Protection Regulation (GDPR) (EU, 2016/679). This research did not receive any
specific grant from any funding body in the public, commercial or non-profit
sectors.During the preparation of this work the authors used Scite.ai. After using this tool/service, the author(s) reviewed and edited the content as needed and took full responsibility for the content of the publication.
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