Analyzing inputs/outputs from the CTC Active Transportation Benefits/Costs tool, to identify and investigate potential issues (analysis notebooks only - input/output data is not included)
(1) Change combined mode such that any interventions with only combined effect sizes get applied to walking and bicycling equally.
(2) Figure out better method for estimating demand of new off street paths.
(3) Conversion from demand to miles traveled: currently we have assumed a constant 25% bike, 30% walk travel is within the project when converting demand to miles traveled. Consider revising this conversion.
(4) Review current evidence of economic benefits (spending in commercial) and job creation(???) from AT projects, consider including as a new quantitative benefit category, or just qualitative if that is all there is available.
(5) Monetization of benefits
(6) Program level functional- list of project IDs in, output Peter report.
(7) update the demand model: could be applying UCB model, or updating our model with UCB data. Probably skip rerunning the PfB accessibility calculations (either use the old ones or drop the variables).
(8) Recreate a clean data pipeline from model results to model prediction, or model prediction to the tool. Coordination on exact data requirements which include a process to update strava network and generate consistent nodeIDs.
(9) Additional calculation changes after convergent validity tests, and results from the SB/SC project.
(1) Change combined mode such that any interventions with only combined effect sizes get applied to walking and bicycling equally. (2) Figure out better method for estimating demand of new off street paths. (3) Conversion from demand to miles traveled: currently we have assumed a constant 25% bike, 30% walk travel is within the project when converting demand to miles traveled. Consider revising this conversion. (4) Review current evidence of economic benefits (spending in commercial) and job creation(???) from AT projects, consider including as a new quantitative benefit category, or just qualitative if that is all there is available. (5) Monetization of benefits (6) Program level functional- list of project IDs in, output Peter report. (7) update the demand model: could be applying UCB model, or updating our model with UCB data. Probably skip rerunning the PfB accessibility calculations (either use the old ones or drop the variables). (8) Recreate a clean data pipeline from model results to model prediction, or model prediction to the tool. Coordination on exact data requirements which include a process to update strava network and generate consistent nodeIDs. (9) Additional calculation changes after convergent validity tests, and results from the SB/SC project.