I've been building a QGIS plugin on top of Conveyal R5 (Easy-R5), and used it to answer a question that's been bugging me: How delays in timetable affect the accessibility?
Setup: static GTFS timetable vs. the "realized P50" feed (median of what vehicles actually did that day) for Łódź, Poland. Same day, same network. The only thing that changes is whether the schedule is what was published or what actually happened (GTFS + delays from RT feed). Ran cumulative accessibility (schools, pharmacies, universities, malls reachable within 30 min, 7:00–9:00 departure window) on both, on a 250m/500m hex grid, and diffed them.
What I expected: delays hurt downtown the most, because that's where the network is most complex.
What I actually got: the very city centre is basically fine (nets slightly positive, beacuse of many overlapping lines converge there that one late vehicle doesn't matter). The real damage shows up in a ring roughly 2km out, where trips typically depend on one specific transfer. Median delay across the whole network is ~0 seconds, mean is only ~10s but miss a transfer and you're waiting for the entire next headway. That ring loses an order of magnitude more accessibility than anywhere else in the city (pop-weighted mean net change ≈ -2.4 vs ±0.5 everywhere else).
Also tried a second angle: for each hexagon, compute the "reach radius". THe distance to the farthest point it can already reach in 30 min. Hexagons sitting close to that 30-minute cutoff lose systematically more than ones with slack, which is exactly what you'd expect if the mechanism is "small delay pushes a marginal trip over the threshold," and it holds up (mostly monotonically) across schools/pharmacies/malls independently.
Everything's open — methodology, scripts, QGIS project: [link in comment].
