How can destinations leverage granular urban data to create more inclusive, accessible and individually meaningful visitor experiences?
The evolution of urban mobility from standardised routing systems to personalised navigation experiences represents a fundamental shift in how destinations can serve diverse visitor needs. Simone Grasso (Systematica) and Lily Scarponi (Transform Transport) share how their multi-user walkability route planner demonstrates how sophisticated spatial data analysis can transform traditional city navigation into user-centric journey design. This research reveals how destinations can leverage granular urban data to create more inclusive, accessible and individually meaningful visitor experiences.
Founded in 2022 as Systematica's research foundation, Transform Transport initially focused on quantitative urban parameters, analysing pavement widths during the COVID-19 pandemic to understand social distancing requirements, mapping thermal comfort zones based on environmental factors and developing accessibility metrics across Milan's urban landscape. This foundational work revealed the limitations of traditional spatial analysis approaches. Whilst quantitative data could effectively map physical infrastructure characteristics, it failed to capture the nuanced human experiences that fundamentally shape how individuals navigate urban environments. The 2020 analysis of pavement width, for instance, successfully identified that 45% of Milan's pavements were inadequate for maintaining social distancing protocols, yet this technical precision could not predict which routes people would actually choose based on comfort levels, cultural norms or individual risk assessments. Similarly, the recognition that thermal comfort, accessibility and safety perceptions vary dramatically across different user groups prompted a methodological evolution toward integrated quantitative-qualitative analysis.
The progression toward the 15-minute city model represented a further significant advancement in methodological sophistication, combining walkability metrics with service accessibility data to reveal distinct patterns of urban equity across Milan's neighbourhoods. Areas like Centrale, Duomo and Garibaldi emerged as highly accessible zones, whilst peripheral areas showed significant service deficits. However, even this detailed spatial analysis could not account for how different demographic groups might experience theoretically optimal routes differently based on safety perceptions, cultural factors or individual mobility constraints. Based on these insights, the organisation's research trajectory illustrated the need for critical evolution from purely data-driven urban analysis to human-centred spatial intelligence.
The shift from quantitative mapping to qualitative understanding reflects a broader transformation in how destinations must approach digital innovation and visitor experience design. Traditional approaches that prioritise technical capability over user experience consistently fail to deliver meaningful improvements in actual destination experiences, regardless of their technical sophistication. For destinations, this evolution demands organisational capabilities that extend far beyond traditional technical expertise to include qualitative research methods, community engagement processes and iterative design approaches that continuously incorporate user feedback.
Transform Transport's experience demonstrates that this methodological evolution, whilst resource-intensive, creates significantly more valuable analytical capabilities that can inform both immediate practical applications and longer-term strategic planning processes. Destinations must develop more refined approaches to data governance and algorithmic design that account for the complex relationships between technical optimisation and human experience. The most sophisticated technical solutions may inadvertently reinforce existing inequalities or accessibility barriers if they fail to incorporate a comprehensive understanding of how different user groups experience urban environments.
The breakthrough toward truly integrated analysis emerged through the STEP UP project, which examined women's perceptions of safety whilst walking at night in Milan. This research represented a fundamental methodological evolution, demonstrating how spatial data analysis could incorporate intersectional considerations that account for the complex interplay between identity factors and urban experience.
The project's methodological sophistication lay in its systematic integration of quantitative spatial data with qualitative experience research collected through surveys, focus groups and participatory mapping exercises. The research team developed frameworks for translating subjective safety perceptions into measurable urban characteristics, creating algorithms that could identify correlations between environmental factors and reported comfort levels across different demographic groups. This approach recognised that gender identity intersects with age, disability status, ethnicity and economic circumstances to create unique urban navigation experiences that cannot be captured through single-variable analysis.
The findings revealed the inadequacy of traditional safety metrics that focus primarily on crime statistics or lighting levels. Women's safety perceptions were influenced by complex combinations of factors, including the presence of active commercial establishments (providing natural surveillance and activity), public transport accessibility, street lighting quality and pedestrian activity levels. The research demonstrated that 59% of Milan's street network could benefit from improvements across three critical areas: food and beverage establishments, public lighting enhancement and improved public transport connections.
Most significantly, the project revealed how individual experiences of urban space result from multiple intersecting factors that traditional quantitative analysis cannot capture. A route that appears optimal in terms of lighting and infrastructure might still feel unsafe to women if it lacks active commercial presence or public transport accessibility. Conversely, routes that appear technically suboptimal might provide superior experiences due to factors such as community presence, cultural familiarity or personal safety associations that exist outside quantitative measurement frameworks. This integrated approach provides destinations with actionable insights that purely technical analysis cannot deliver. These insights enable destinations to develop more effective infrastructure investment strategies that address the actual factors influencing visitor experience rather than abstract technical optimisation criteria.
The multi-user walkability route planner represents an elaborate response to the fundamental insight that "there's no universal route; only personal journeys". This route planner transcends conventional navigation systems by integrating twelve distinct walkability indicators with user preference data to generate personalised routing solutions. The framework demonstrates how destinations can move beyond one-size-fits-all approaches to create navigation systems that adapt to individual needs and circumstances.
The methodology's strength lies in its systematic integration of diverse data sources with visitor preferences. The system incorporates physical infrastructure data (pavement width and quality, slope measurements), environmental conditions (air quality, thermal comfort, greenery levels) and social factors (lighting quality, traffic levels, pedestrian area availability). Rather than applying predetermined weightings to these factors, the system enables users to dynamically adjust their preferences, creating personalised routing algorithms that reflect individual priorities and constraints.
This approach generates demonstrably different navigation experiences. When testing routes between identical points in Milan, the system produced paths ranging from the standard 3.8-kilometre shortest route to user-optimised alternatives extending to 6.2 kilometres. In adding a variable focused on desired route length, the system's optimisation capabilities enabled users to balance their preferences against distance constraints, creating routes that were 24% longer than the shortest path whilst maintaining 89% of user-specified environmental and accessibility preferences.
The visualisation strategy addresses the critical challenges of making complex, multi-dimensional information accessible to non-specialist users. The system's interface employs intuitive slider controls that enable users to adjust preferences across twelve parameters whilst simultaneously displaying how these adjustments affect route characteristics through dynamic visual feedback. This approach democratises access to sophisticated spatial analysis capabilities whilst maintaining the system's technical sophistication.
The bubble visualisation system provides particularly effective communication of route performance across multiple parameters. By representing indicator strength through bubble size and distributing these visual elements along proposed routes, users can immediately understand how different path options perform across their prioritised criteria. This visualisation approach transforms abstract spatial data into actionable navigation information whilst maintaining transparency about the trade-offs inherent in different routing choices.
The transition from prototype to operational system reveals significant challenges in data availability, quality and maintenance that destinations must address to implement sophisticated spatial navigation solutions. Creating these datasets requires significant investment in both technological infrastructure and human expertise for data collection, validation and maintenance processes. Computer vision systems, geomapping technologies and qualitative research methodologies must work in coordination to create datasets that accurately represent both physical infrastructure and user experience factors.
The system's effectiveness depends on developing governance frameworks that maintain current, accurate information across the twelve parameters. This must include continued environmental monitoring, infrastructure assessment and ongoing user experience research. The potential integration of real-time data introduces additional complexity, but presents enormous potential for helping modify routing suggestions based on peak visitation periods, weather, temporary accessibility barriers or special events to distribute visitor flows more effectively and create a personalised experience ecosystem. In doing so, such approaches would enable win-win scenarios for maintaining visitor experience quality whilst supporting broader destination management objectives.
At the same time, the development of personalised navigation systems raises important questions about algorithmic bias, data representation and equitable access to urban spaces. The UX framework addresses these concerns through user-controlled preference settings rather than predetermined demographic profiling, mitigating algorithmic bias by avoiding assumptions about user needs. However, the underlying spatial data itself may reflect existing urban inequalities, potentially reinforcing accessibility barriers or safety concerns rather than addressing them. With this in mind, destinations implementing such systems must consider how routing algorithms might inadvertently direct certain user groups away from particular areas. Understanding the digital divide, with technical literacy and device compatibility as two primary considerations, becomes particularly important in ensuring all visitors can access the navigation systems for urban exploration.
Researcher
Fondazione Transform Transport ETS
Project Lead
Systematica
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