A cross-disciplinary study by VUB researchers has blended data science with mobility expertise to identify 30 major bottlenecks in the Brussels cycling network where segregated bike lanes are critically missing.
Developed by researchers Sara Tori and Floriano Tori, the innovative method combines static government data with anonymised tracking from the sports app Strava. Traditional infrastructure planning relies heavily on manual counts or Brussels’ 18 fixed counters, which are only located where cycle paths already exist, creating a major data blind spot.
By training a machine learning algorithm to link fixed counter data with widespread Strava activity, the team successfully modelled realistic cycling volumes for every street in the capital. The analysis focused specifically on roads lacking safe, segregated infrastructure, highlighting two critical priority zones: missing links (where bike lanes abruptly end) and new arteries (high-volume cycling streets that lack safe paths).
With this research, mobility planners have an objective tool to maximise the 'Return on Investment' of new cycle lanes, where it is up to policymakers to identify what the return should be (increased safety, increased cycling volumes,...). Based on the results, the government can now invest further in those places where cyclists are already massively present today, but where their safety is not yet guaranteed.
Read the full press release.
- Watch the video report by Bx1.
- Read the articles by Bruzz, Bx1, Brussels Times, Nieuwsblad, RTBF.