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@Robinlovelace I've been through all of your excellent code for adapting the PCT approach to scenario modelling, and am pretty confident that it all adapts fairly directly to network-level analyses. I also (finally) understand the way that scenarios are constructed, and the way they depend on the fundamental distribution of bicycle trip distances. And so this issue is to ask whether it might be possible for you to use the NTS data you used for the analysis of walking trips per hour to generate an equivalent distribution of either times or lengths (or, even better, both!)?
Given that, i should be able to fairly quickly adapt the general PCT approach to modelling cycling propensity and demand to pedestrian behaivour, and generate realistic scenarios for changes in walking behaviour in response to the addition of bus stops.
The text was updated successfully, but these errors were encountered:
@Robinlovelace I've been through all of your excellent code for adapting the PCT approach to scenario modelling, and am pretty confident that it all adapts fairly directly to network-level analyses. I also (finally) understand the way that scenarios are constructed, and the way they depend on the fundamental distribution of bicycle trip distances. And so this issue is to ask whether it might be possible for you to use the NTS data you used for the analysis of walking trips per hour to generate an equivalent distribution of either times or lengths (or, even better, both!)?
Given that, i should be able to fairly quickly adapt the general PCT approach to modelling cycling propensity and demand to pedestrian behaivour, and generate realistic scenarios for changes in walking behaviour in response to the addition of bus stops.
The text was updated successfully, but these errors were encountered: