Validate flow estimates for walking and cycling

[Robinlovelace]

For each mode.

[mpadge]

Note that Brutus (#11) analyses flows between 11 types of destinations: own home, own work, other residential/visit place, work related visit, own school, “kiss&ride”, day care, shopping, restaurant, sport/culture/other free time place. Our layers cover all of those, which is good.

[mpadge]

@Robinlovelace New, usable data for Kathamandu in who-data repo - yep, that's moveability data. This code is far more up-to-date, and works really well. I now need to update the old flowlayers code to function like moveability. The results look much better than any previous attempts at flow layers for Kathmandu:

Those data should be able to be plugged straight in to upthat - a task that intend to tackle myself first thing tomorrow morning.

[Robinlovelace]

Hey @mpadge that looks great to me! Many thanks, looks awesome. I plan to set-up a traffic flow validation repo in ITSLeeds that we can use for multi modal flow estimate validation using data from

• here for motor vehicles: https://data.gov.uk/dataset/9562c512-4a0b-45ee-b6ad-afc0f99b841f/highways-england-network-journey-time-and-traffic-flow-data

• here for motor vehicles and other modes: https://roadtraffic.dft.gov.uk/downloads

[Robinlovelace]

Update for @mpadge: here's a place where I've created a 'visualisation challenge': https://github.com/ITSLeeds/trafficEstimatr

[mpadge]

It's private ...

[Robinlovelace]

Yes - feel free to take code from there to validate the flows. Or is it that you cannot see the repo? It thought you were in the organization.

[mpadge]

I can't see it 🙈

[Robinlovelace]

Apologies, my bad!

[Robinlovelace]

Just added you: https://github.com/ITSLeeds/trafficEstimatr/invitations

[Robinlovelace]

🚶‍♂️ 🚲 🚀

[mpadge]

Calibration of bicycle estimates can be done via bikedata. Calibration of pedestrian estimates can be done using the following sources of open data:

Number	Location	Number of Counters	Notes
1	New York City	114	Very extensive spatial coverage all 5 Boroughs
2	Melbourne	53	Descrbied here, but very spatially restricted to inner city only
3	Kansas City	610
4	Auckland	19
5	Louisville KY	49
6	Toronto CA	2,280

New York could then be used as a benchmark city for both bicycle and pedestrian flows, and Kansas City is clear preference for pedestrian flows - much smaller that NYC and much higher density data.

current plan:

Flow layer	City	✔️
pedestrians	NY	✔️
pedestrians	Kansas	✔️
bikes	NY	✔️
bikes	(somewhere else)	❓

A good additional bike city might be Guadalajara, because at least that is somewhat beyond the Global North.

[mpadge]

@Robinlovelace Very first try at moveability versus actual pedestrian counts across New York City, noting that moveability is not intended to model such things at all:

Relationship is definitely positive and highly significant (p = 0.002).

[Robinlovelace]

Looking good! Shows that measuring pedestrian flows is hard. Results from another paper using the recently open sourced sDNA package: