Priority weightings compared

weightings.R

PRIORITY_CODE = c(
  WORST = 0,
  AVOID_AT_ALL_COSTS = 1,
  REACH_DEST = 2,
  AVOID_IF_POSSIBLE = 3,
  UNCHANGED = 4,
  PREFER = 5, 
  VERY_NICE = 6,
  BEST = 7
)

## priority values returned by the priority encoder
priority <- function(code) code / unname(PRIORITY_CODE["BEST"])

sapply(PRIORITY_CODE, priority)
#>              WORST AVOID_AT_ALL_COSTS         REACH_DEST  AVOID_IF_POSSIBLE 
#>          0.0000000          0.1428571          0.2857143          0.4285714 
#>          UNCHANGED             PREFER          VERY_NICE               BEST 
#>          0.5714286          0.7142857          0.8571429          1.0000000

## original weight scaling function
priorityWeighting <- function(x) 1 / (0.5 + priority(x)) 

## current recommended weighting
optimizedPriorityWeighting <- function(x) {
  best = PRIORITY_CODE["BEST"]
  val = priority(x) * best - ceiling(best/2)
  2^(-val/3) 
}

## original weight scaling function
preferencePriorityWeighting <- function(x) {
  p <- priority(x)
  if (x <= PRIORITY_CODE["REACH_DEST"])
    p = p / 1.5
  else if (x <= PRIORITY_CODE["AVOID_IF_POSSIBLE"])
    p = p / 1.25
  else if (x == PRIORITY_CODE["PREFER"])
    p = p * 1.5
  else if (x >= PRIORITY_CODE["VERY_NICE"])
    p = p * 2.2;
  
  1 / (0.5 + p) 
}

renderPlots <- function(main, log = "") {
  pch = c(16, 1, 4)
  col = c("black", "red", "blue")
  plot(PRIORITY_CODE, sapply(PRIORITY_CODE, priorityWeighting), pch = pch[1], col = col[1], ylim = c(0.25, 4), ylab = "weight scaling factor", main = main, log = log)
  points(PRIORITY_CODE, sapply(PRIORITY_CODE, optimizedPriorityWeighting), pch = pch[2], col = col[2]) 
  points(PRIORITY_CODE, sapply(PRIORITY_CODE, preferencePriorityWeighting), pch = pch[3], col = col[3])
  legend("topright", c("GraphHopper", "OptimizedPriorityWeighting", "PreferencePriorityWeighting"), pch = pch, col = col, cex = 0.8)
}

## linear scale
renderPlots("Linear scale")

## log scale
renderPlots("Logarithmic scale", "y")