Amsterdam Is Building Tools to Track How People Actually Walk Through the City
Amsterdam, Saturday, 30 May 2026.
A Dutch research consortium is developing data-driven tools to map pedestrian movement in Amsterdam, revealing critical gaps in how cities currently understand foot traffic.
A Consortium With a Clear Mission
The effort is not the work of a single institution acting alone. Between 2024 and 2026, the DRO-DMI consortium — comprising the Amsterdam Institute for Advanced Metropolitan Solutions (AMS Institute), the municipalities of Amsterdam and Almere, Groningen Bereikbaar, Goudappel, Technolution, and ViaNova — has been funding 20 Proof of Concept (PoC) projects, co-funded by the Nationaal Groeifonds, to develop digital, data-driven solutions for urban mobility [1]. The AMS Institute, which sits at the heart of this initiative, describes its core mandate as designing solutions for urban challenges and educating the next generation of engineers, with a specific focus on researching and valorizing interdisciplinary metropolitan solutions for the city of Amsterdam [1]. The scale of the consortium — spanning research institutes, technology firms, and multiple municipal governments — signals how seriously Dutch cities are taking the question of urban movement data, and how much institutional weight is now behind solving it.
The Pedestrian Flow Model: How It Works
In May 2026, the DRO-DMI consortium published a policy paper detailing a Pedestrian Flow Model — known in Dutch as the Loopstromenmodel — developed jointly by the AMS Prototyping Team, TU Delft, and Wageningen University & Research [1]. The model is not simply a more detailed version of existing pedestrian count tools. Instead, it introduces a set of methodological advances designed to address the specific ways conventional models fail. The prototyping team developed methods to improve pedestrian flow models by explicitly modeling busy origin-destination flows, correcting model deviations, and linking walking space and capacity bottlenecks to prioritize space allocation between pedestrians, cyclists, and motorized traffic [1]. In practical terms, this means city planners can move beyond asking how many people passed a given point and begin answering far more nuanced questions: where are people coming from, where are they going, and where does the system break down under pressure? The model is designed for direct integration into municipal workflows, GIS environments, and digital twin platforms, making it actionable rather than merely academic [1].
Walkability, Wheelchair Users, and the Gaps Conventional Data Misses
The consortium’s ambitions extend beyond aggregate flow modeling. A separate Proof of Concept, CTstreets, developed as a walkability analysis tool tailored for urban planners, designers, and policymakers, was built using a four-layer framework focusing on user-centered development and translating insights into concrete action to design safer, more walkable streets [1]. The tool was developed with a July 2026 [alert! ‘source states July 23, 2025 as the development date for CTstreets PoC; article date is May 30, 2026 — timeline treated as background context’] background timeline in view, reflecting ongoing iterative development within the consortium’s 2024–2026 funding window. Equally significant is a third Proof of Concept focused on underrepresented groups: to map pedestrian movement among people who are often invisible in standard mobility datasets, researchers designed a privacy-conscious tool that collected mobility data from wheelchair users using GPS tracking, in-app surveys, and interviews [1]. This recognizes a structural gap in urban data collection — that the people for whom street-level conditions matter most are frequently the least represented in the models used to design those streets [GPT].
Scaling Up: From Amsterdam to Dutch Municipalities
The consortium is not treating these tools as research endpoints. Key findings and prototypes from the Proofs of Concept are being scaled up and shared with Dutch municipalities through DRO-DMI and Open Research Amsterdam, with the explicit goal of embedding these tools into existing municipal workflows, GIS environments, and digital twin platforms [1]. This distribution strategy matters: the value of a pedestrian flow model is multiplied when it is adopted not just by Amsterdam but by the other cities represented in the consortium, including Almere and those connected through Groningen Bereikbaar [1]. The broader Dutch urban planning community stands to benefit from tools that are designed from the outset to be interoperable with the systems municipalities already use. Amsterdam, in this framing, is not simply a beneficiary of smart mobility innovation — it is functioning as the living laboratory through which these tools are being stress-tested before wider rollout [1].
What This Means for Urban Planning
The significance of this work lies in what it makes possible downstream. When city planners have granular, reliable data on pedestrian origin-destination flows, they can make evidence-based decisions about where to widen pavements, how to sequence pedestrian signals, where cycling and walking routes conflict, and how to design last-mile connectivity from transit stops [1][GPT]. The integration of wheelchair user mobility data adds a layer of equity analysis that has historically been absent from urban mobility modeling [1]. For a city like Amsterdam — navigating the simultaneous pressures of population growth, sustainability commitments, and the need to preserve street-level livability — these tools represent a meaningful step toward infrastructure decisions grounded in how people actually move, rather than how planners have historically assumed they do [1]. The Nationaal Groeifonds co-funding also signals that the Dutch national government sees data-driven urban mobility as a strategic investment, not a niche research exercise [1].