Using A/B Street to show micro examples of transport policy #691
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If you start with a scenario (travel demand model), you can randomly change some percentage of people to use a different mode. https://a-b-street.github.io/docs//user/asu.html#modifying-a-scenario has instructions for doing this. If you can get the baseline simulation to run without gridlock, then you can measure relative changes with this 5% shift scenario -- like which trips get faster or slower, and if people encounter more or less safety issues on their trip. Which 5% of drivers would switch to buses, though? Probably ones who live near a bus route that you're interested in improving? If this is what you're interested in, luckily I'm soon starting work on mode shifting in response to changes to a map. There's a huge design space for deciding when somebody will decide to change modes, though -- how do you give a score for taking transit vs driving for one trip? How much better do you have to shift that score to convince someone to switch? If you're specifically interested in modeling people using buses, currently that support isn't ready. @tnederlof is just now looking into importing bus routes from GTFS. We had an earlier implementation using routes from OpenStreetMap, but it's broken. Any more specifics about what you'd like to try -- what city, what kind of comparison (the 5% shift? or editing the map to convince 5% of people to shift?), and what kind of measurements you'd like to get? |
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We've been discussing using A/B street to showcase small subsets of a transport system to show how specific optimisations might lead to different outcomes. Say, showing how moving 5% of car drivers on to buses eliminates congestion. How easy would it be to build such scenarios with A/B street?
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