#' \code{zipperwrapper} produces \code{t-x} trajectory for vehicles traveling on parallel lanes that merge at a bottleneck.
#'
#' @return The \code{zipperwrapper}, a wrapper function for \code{bmfree3}, \code{xabparam} and
#' \code{hsafe}, returns a smooth \code{hsafe} rule \code{t-x} trajectory
#' for the following vehicle, and critical information. The lead vehicle trajectory is not affected. Passing is not permitted.
#' The input matrix \code{lane} contains desire lines for a leading and following vehicle.
#' @param nveh1 number of vehicles entering the bottleneck from lane 1, a number
#' @param nveh2 number of vehicles entering the bottleneck from lane 2, a number
#' @param umn start speed (mph) for vehicle in lane 1, a number
#' @param usd speed standard deviation, a number
#' @param xstart1 start location of the first vehicle in lane 1, (feet), a number
#' @param xstart2 start location of the first vehicle in lane 2, (feet), a number
#' @param delt time-step, a number
#' @param tstart vehicle crossovers are are permitted below this time, a number
#' @param tend upper time range of simulation, a number
#' @param xfunnel location where the lane drop is located, a number
#' @param leff vehicle length in feet, a number
#' @param type TRUE to create plots or FALSE otherwise, a logical
#' @param browse to inspect \code{fixviolation} to inspect plot or FALSE otherwise
#' @usage zipperwrapper(nveh1,nveh2,umn,usd,xstart1,xstart2,delt,tstart,tend,xfunnel,leff,type,browse)
# #' @examples
# #' zipperwrapper(nveh1,nveh2,umn,usd,xstart1,xstart2,delt,tstart,tend,xfunnel,leff,type,browse)
#' @export
zipperwrapper <- function(nveh1,nveh2,umn,usd,xstart1,xstart2,delt,tstart,tend,xfunnel,leff,type,browse) {
#### STEP 1. Create lane 1 and 2 datasets ################################################################
# set.seed(123)
# set.seed(403)
# set.seed(333)
xlim <- c(tstart,tend)
print(data.frame(nveh1,nveh2,umn,usd,xstart1,xstart2,delt,tstart,tend,xfunnel,leff,type,browse))
df1df2 <- zippermerge(nveh, tstart, tend, xstart1, umn, leff, xfunnel, delt, type)
print(df1df2[1:10,])
# browser()
#### STEP 2. Order vehicles by the times that they reach x = 0 ####################
index <- matrix(seq(2,dim(df1df2)[2]),ncol = 3, byrow = TRUE)
index <- cbind(veh = seq(1,nveh), index)
lane1veh <- seq(1,nveh,2)
index1 <- as.vector(index[lane1veh,2:4])
o <- order(index1)
index1 <- index1[o]
lane1 <- df1df2[,index1]
lane2veh <- seq(2,nveh,2)
index2 <- as.vector(index[lane2veh,2:4])
o <- order(index2)
index2 <- index2[o]
lane2 <- df1df2[,index2]
lst <- enterbottleneck(lane1,lane2,xfunnel,tend,delt)
dfcrit <- lst[[1]]
nveh <- lst[[2]]
print(dfcrit)
#### STEP 3. Merge lane 1 and 2 data sets ##########################################
tend.0 <- tend
tseq <- seq(0, tend, delt)
tlen <- length(tseq)
df1df2 <- mergedata(lane1,lane2,tlen,dfcrit)
# Zone violations
for(veh in 1:(nveh)) {
for(zone in 1:3) {
dfcrit <- zoneviolation(veh, zone, df1df2, dfcrit, delt, tend.0, leff)
}
}
print(dfcrit)
#### STEP 6. Flow Estimation ######################################################
lst <- flow(df1df2, tstart, tend, delt, xfunnel)
df1 <- lst[[1]]
df2 <- lst[[2]]
if(type == TRUE) {
par(mfrow = c(1,2), pty = "s")
plot(df1[,2], df1[,1], typ = "s", xlim = c(0,max(df1[,3])), ylim = c(1,nveh+0.1),
ylab = "Vehicle", xlab = "t, seconds", col = "red", lwd = 2)
lines(df1[,3], df1[,1], typ = "s", col = "orange", lwd = 2)
abline(v = 0, col = gray(0.8))
abline(h = 1, col = gray(0.8))
sub = ""
if(usd == 0) sub <- "Side-by-side merge." else sub <- "Unmanaged zipper merge."
title(main = "Bottleneck", sub)
# axis(side = 3, at = max(df1[,3])/2, sub, tick = FALSE, line = -1)
legend("topleft", legend = c("A = arrival","D = departure"), lty = c(1,1), col = c("red","orange"), bty = "n")
u.a.mean.mph <- as.numeric(df2[1])
u.d.mean.mph <- as.numeric(df2[2])
}
#### STEP 7. Capacity Estimation
df1 <- flow2(dfcrit, df1df2, tstart, tend, delt, xfunnel)
tservice = abs(round(xfunnel/(5280/3600*umn),1))
if(type == TRUE) {
xlim <- c(0, 200)
ylim <- c(0, 4000)
plot(df1[,7], df1[,8], typ = "p", xlim, ylim, ylab = "q, vph",
xlab = "k, vpm", pch = 16, cex = 1, col = "orange")
points(df1[,10],df1[,11], pch = 16, col = "red")
sub = expression("Service time: "*W(t) == D(t) - A(t))
title(main = "Bottleneck" , sub)
k.d.mn <- round(mean(df1[,7], na.rm = TRUE),0)
q.d.mn <- round(mean(df1[,8], na.rm = TRUE),0)
k.a.mn <- round(mean(df1[,10], na.rm = TRUE),0)
q.a.mn <- round(mean(df1[,11], na.rm = TRUE),0)
w.mn <- round(mean(df1[,6], na.rm = TRUE),1)
axis(side = 3, at = k.a.mn, labels = expression(bar(k)[A]), tick = FALSE, line = -1)
axis(side = 3, at = k.d.mn, labels = expression(bar(k)[D]), tick = FALSE, line = -1)
abline(h = 0, col = gray(0.8))
abline(v = 0, col = gray(0.8))
abline(h = q.a.mn, lty = 2, col = "orange")
abline(h = q.d.mn, lty = 2, col = "red")
abline(v = k.a.mn, lty = 2,col= "orange")
abline(v = k.d.mn, lty = 2,col= "red")
axis(side = 4, at = q.d.mn, labels = expression(bar(q)[D]), tick = FALSE, line = -0.75)
axis(side = 4, at = q.a.mn, labels = expression(bar(q)[A]), tick = FALSE, line = -0.75)
u.a.mean.mph <- round(mean(as.numeric(df1[,9])),1)
u.d.mean.mph <- round(mean(as.numeric(df1[,12])),1)
legend("topright",
legend = c(
"A = arrival",
"D = departure"
),
cex = c(1,1),
col = c("red","orange"),
pch = c(16,16), bty = "n"
)
legend("bottomright",
title = "",
legend = c(
expression("Predictions:"),
bquote(bar(u)[A] == .(u.a.mean.mph)),
bquote(bar(u)[D] == .(u.d.mean.mph)),
bquote(bar(w) == .(w.mn)),
bquote(t[server] == .(tservice))
),
cex = c(0.75,0.75,0.75,0.75)
)
}
print(df1)
browser()
return(df1df2)
}
##############################################################################################
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.