As cities worldwide embrace micromobility such as e-scooters, bicycles, and other lightweight modes, they are also confronted with new safety challenges. While these modes expand accessibility and sustainable transport options, their interaction withvehicles, public transport vehicles and urban infrastructure introduces risks that are not always captured by traditional traffic data. To design truly safe and inclusive mobility systems, cities need reliable, contextual, and privacy-respecting methods for detecting and addressing these risks.
This session will present an innovative real-world case study from Rotterdam, where smart traffic sensors known as Flowcubes were deployed to understand and mitigate near-collision risks between micromobility users and trams. Unlike conventional monitoring approaches, Flowcubes were installed both on static infrastructure (such as intersections) and on moving trams, creating a comprehensive network of vantage points. This configuration enabled the detection of near-miss events, collection of key incident characteristics, and storage of short, privacy-blurred video snippets for further context.
The data pipeline is both robust and practical: Flowcubes continuously recorded near-misses, classified the involved modes, estimated risk levels, and logged frequencies and locations. These insights were visualized in a dashboard, which highlighted hotspots along tram corridors where risky interactions recurred. Decision-makers could then explore anonymized video snippets to contextualize whether a single incident reflected random behavior, or pointed to structural design flaws in the infrastructure.
DTSTAMP;VALUE=DATE-TIME:20260320T225425 DTSTART;VALUE=DATE-TIME:20260310T120000 DTEND;VALUE=DATE-TIME:20260310T123000 LOCATION:ROAD SAFETY STAGE SUMMARY;LANGUAGE=en_us:Safe urban infrastructure for all modes: let's act before accidents happen TRANSP:TRANSPARENT END:VEVENT END:VCALENDAR