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Resources, scripts, and how-tos for calculating national travel time matrices
The input/
directory contains pre-calculated origins and destinations for 2010 Census tracts and ZCTAs. We should update it to include OD pairs based on 2020 Census geographies.
NOTE: The 2010 OD pairs are population-weighted centroids. These are calculated using the census block population counts available here. It seems like these block-level counts have not yet been released for 2020, so we may have to wait a bit.
Below is a plot of multi-model travel times in Cook County with the following settings:
Starting census tract = 17031031502
Departure time = 2021-04-16 20:21:17 CDT
Maximum walking distance = Infinite
Maximum trip duration = 600 minutes
Maximum number of rides = 5
Transit modes = TRANSIT (any mode) + WALKING
Destinations = All census tracts in Illinois ( + a 100 km buffer) reachable with 600 minutes
Walk speed = 3.6 km/h
The times and structure here look pretty reasonable to me. However, the sharp discontinuities (quick changes from purple/blue to yellow) really shouldn't be possible. I suspect they have something to do with the OSM network in the area, or maybe the walk speed is too low.
We should start to collect metadata on GTFS feeds (and corrective actions) used in this project in order to ensure reproducibility. Metadata can be stored in a simple flat file in inputs/shared/feeds
and could contain fields such as date feed last updated (on TransitFeeds), feed location, feed name, list of potential errors/issues, and a list of corrective actions taken to fix said issues.
Potential feed issues include:
We may even want to compile a collection of validated feeds + metadata and tarball it in this repo. This would ensure reproducibility but would be a lot of work.
For feed validation, I've used this tool in the past. Google also has a tool here. Rafa also mentions they're working on a gtfstools R package specifically for this purpose.
Create a README file with:
Occasionally, r5r will generate a travel times matrix with an unroutable destination in the middle of an otherwise routable area. In the case of census tracts, this will appear as a grey (missing value) tract in the middle of an otherwise complete isochrone.
Destinations can be unroutable for a variety of reasons, including:
We should investigate and try to fix each of these potential issues. However, my experience with OTP tells me that we'll likely always have some gaps in our output matrices. Rafa's team suggested taking an average of touching destination polygons to fill in gaps.
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