E-bikes scenario

knitr::opts_chunk$set(eval = FALSE, include = FALSE)
library(biclar)

public policies to increase e-bike usage.

# check analysis with dplyr and estimation of cycling uptake with pct function

library(pct)
route_segments_balanced = sf::read_sf(u3)
routes_balanced = route_segments_balanced %>% 
  group_by(DICOFREor11, DICOFREde11) %>% 
  summarise(
    Bike = mean(Bike),
    All = sum(Total),
    Length_balanced_m = sum(distances),
    Hilliness_average = mean(gradient_segment),
    Hilliness_90th_percentile = quantile(gradient_segment, probs = 0.9)
  ) %>% 
  sf::st_cast("LINESTRING")
summary(routes_balanced$Length_balanced_m)
routes_balanced$Potential = pct::uptake_pct_godutch( #here goes our ENMAC function!
  distance = routes_balanced$Length_balanced_m,
  gradient = routes_balanced$Hilliness_average
    ) * 
  routes_balanced$All

rnet_balanced = overline(routes_balanced, "Potential")
b = c(0, 0.5, 1, 2, 3, 8) * 1e4
tm_shape(rnet_balanced) +
  tm_lines(lwd = "Potential", scale = 9, col = "Potential", palette = "viridis", breaks = b)