Mode split of utility trips under the baseline scenario

[Robinlovelace]

Currently we have the following:

npt/_targets.R

Lines 806 to 830 in f420b5f

	cycling_multiplier = commute_stats_minimal |>
	dplyr::transmute(
	DataZone,
	multiplier = (comm_orig_bicycle / comm_orig_all) /
	pcycle_national
	) |>
	# 0 to 0.1:
	dplyr::mutate(multiplier = case_when(
	multiplier == 0 ~ 0.1,
	TRUE ~ multiplier
	))
	# summary(cycling_multiplier$multiplier)
	# Add new cycling multiplier column to od_utility_combined
	od_utility_combined = od_utility_combined |>
	dplyr::left_join(cycling_multiplier, by = join_by(geo_code1 == DataZone)) |>
	# Convert NAs to 1:
	dplyr::mutate(multiplier = case_when(
	is.na(multiplier) ~ 1,
	TRUE ~ multiplier
	)) |>
	dplyr::mutate(
	bicycle_new = bicycle * multiplier,
	car = car - (bicycle_new - bicycle),
	bicycle = bicycle_new
	) |>

Ideas for improving:

• Make the % cycling under baseline dependent on the distance and maybe also hilliness
  • Idea on that: we could use the baseline function in PCT to generate a distance_multiplier similar to the zonal multiplier added in Update utility methods report (#470) #474
  • Idea on that: use data from nearby cycle counters to get an estimate of cycling activity recently