1. library(shiny)
library(shinythemes)
library(dplyr)
library(ggplot2)
library(radiant.data)
library(radiant.model)
library(ggvis)
library(ggplot2)
library(ggmap)
library(gridExtra)
library(googleVis)
library(plotly)
library(DT)
library(leaflet)
# library(radiant.design)
# library(radiant.basics)
# library(radiant.multivariate)
# library(mvtnorm)
# library(radiant)
# Reading in the required datafiles from the source
time.parameter <- read.csv("timeparameter.csv")
safety.parameter <- read.csv("safetyparameter.csv")
cost.parameter <- read.csv("costparameter.csv")
cost.parameter.dropped <- cost.parameter[,c(-6,-7,-8)]
final.results <- read.csv("Finalresults.csv")
final.safety.results <- read.csv("Finalsafetyresults.csv")
final.cost.results <- read.csv("Finalcostresults.csv")
final.time.results <- read.csv("Finaltimeresults.csv")
final.weighted.data <- read.csv("Finalweighteddata1.csv")
all.location <- read.csv("Location.csv")
locations <- all.location[1:30,]
locations$Location <- gsub(",",":",locations$Location)
placeNames <- as.character(locations$Intersection)
plotData <- data.frame(name = placeNames, latLong = unlist(locations$Location))
volume.by.year <- read.csv("~/Desktop/firstpanel/volumeByYear.csv")
volume.by.year.1 <- volume.by.year[,1:10]
volumeByYear <- read.csv("~/Desktop/firstpanel/volumeByYear.csv")
volumeByYear2013 <- volumeByYear[1:30,]
social.good.2016 <- read.csv("~/Desktop/firstpanel/socialgood.csv")
final.weighted.data <- read.csv("Finalweighteddata1.csv")
final.weighted.data.table <-
final.weighted.data[,c("Intersection","Time.100","Cost.100","Safety.100","Total.100", "Rank")]
radius <- final.weighted.data$size*8

2. color <- colorFactor(c("#00FF00","#FFFF00","#FF0000"), final.weighted.data$DDI.Requirement)
popus <- paste(sep = "<br/>",
"Intersection:",
final.weighted.data$Intersection,
"Ranking:",
final.weighted.data$Rank,
"Total Score:",
final.weighted.data$Total.100)
m <- leaflet(final.weighted.data) %>%
addTiles('http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png', attribution='Map tiles by
<a href="http://stamen.com">Stamen Design</a>, <a
href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a> &mdash; Map data &copy;
<a href="http://www.openstreetmap.org/copyright">OpenStreetMap</a>')
m %>% setView(-96.8, 32.7833333, zoom = 8)
m %>% addCircles(lng= ~lng, lat= ~lat , popup=popus, weight = 7, radius=radius, color=
~color(DDI.Requirement), stroke = TRUE, fillOpacity = 0.8)
# # Variables that can be put on the x and y axes
# axis_vars <- c(
# "Time" = "Time",
# "Cost" = "Cost",
# "Safety" = "Safety",
# "Total" = "Total",
# "Ranking" = "Ranking"
# )
# ------------- GRAPHS BASIC -------------------- #
ddi.distance <- c(2,3,8,10,12,14)
ddi.cost.per.mile <- c(2000000,8000000,16000000,20000000,24000000,28000000)
cost.of.construction.per.mile <- data.frame(ddi.distance, ddi.cost.per.mile)
intersections <- c('DNT/635', 'DNT/Alpha', 'DNT/Spring Valley', 'DNT/Beltine', 'DNT/Keller
Springs', 'DNT/Trinity MIlls', 'DNT/Frankford','DNT/PGBT','DNT/Park','DNT/Parker',
'DNT/Windhaven','DNT/Spring
Creek','DNT/Legacy','DNT/SRT','DNT/Gaylord','PGBT/Preston','SRT/Preston','PGBT/75',
'PGBT/Royal Rd','PGBT/Old Denton Rd','PGBT/Independence Rd','PGBT/SH 78','SRT/McArthur
Blvd','SRT/Hebron Pkwy','SRT/Parker Rd','SRT/Marchant Blvd','SRT/Josey
Ln','SRT/Parkwood','SRT/Coit Rd','SRT/Stacy Rd')
type.of.intersection <- c("cloverleaf", "flared", "flared","flared","flared","flared","flared",
"cloverleaf", "flared", "flared", "flared", "flared", "flared", "cloverleaf", "flared","flared",
"flared","cloverleaf","flared","flared","flared","cloverleaf",
"flared","flared","flared","flared","flared","flared","flared","flared")

3. intersection.type <- data.frame(intersections, type.of.intersection)
intersection.type$points <- ifelse(intersection.type$type.of.intersection=="cloverleaf", 74.5,
77.8)
# Calculating the increase in points if a DDI (83.6) is built based on the type of intersection
intersection.type$ddi <- ifelse(intersection.type$type.of.intersection=="cloverleaf", 9.1, 5.8)
# Conditional statement to see which intersections can be converted to a DDI
intersection.type$ddi.possibility <- ifelse(intersection.type$type.of.intersection=="cloverleaf",
"NO","YES")
intersection.type.modified <- subset(intersection.type, ddi.possibility == "YES")
# ------------- GRAPHS BASIC -------------------- #
# ------------------------- Creating Outputs required for PANEL 1 ---------------- #
# Creating an output in the data tab
shinyServer(function(input, output) {
output$time.data <- renderTable({
colm <- as.numeric(input$time.parameters)
time.parameter[colm]
})
output$safety.data <- renderTable({
colm <- as.numeric(input$safety.parameters)
safety.parameter[colm]
})
output$cost.data <- renderTable({
colm <- as.numeric(input$cost.parameters)
cost.parameter[colm]
})
# ------------------------- END OF TABLE RENDERING ---------------- #
# ------------------------- Creating Outputs required for PANEL 2 ---------------- #
# Filter data based on selections
output$table <- DT::renderDataTable(DT::datatable({
data <- time.parameter
if (input$intersections != "All") {
data <- data[data$Intersections == input$intersections,]
}
if (input$exist.lane.length != "All") {
data <- data[data$Existing.Lane.Length == input$exist.lane.length,]
}
if (input$left.turns != "All") {

4. data <- data[data$Lefts == input$left.turns,]
}
data
}))
# ------------------------- END OF TABLE RENDERING for PANEL 2 ---------------- #
# ------------------------- BEGIN PANEL 3 --------------------------- #
result <- explore(dataset = "time.parameter", vars = c("X..of.left.turns",
"Hours.wasted.in.traffic", "Annual.hours.wasted.in.traffic", "Average.Daily.Total.Traffic",
"Speed.Limit", "Existing.Lane.Length"), fun = c("length", "mean_rm", "sd_rm", "min_rm",
"max_rm"), nr = 8)
time.table <- result$tab
output$time.table <- renderTable({
colm <- as.numeric(unlist(input$time.summary))
time.table[colm]
}
)
result <- explore(dataset = "cost.parameter.dropped", vars = c("Hours.wasted.in.Traffic",
"Existing.Lane.Length", "Shoulder.Width"), fun = c("length", "mean_rm", "sd_rm", "min_rm",
"max_rm"), nr = 8)
cost.table <- result$tab
output$cost.table <- renderTable({
colm <- as.numeric(unlist(input$cost.summary))
cost.table[colm]
}
)
result <- explore(dataset = "safety.parameter", vars = c("Number.of.right.lanes",
"Number.of.left.lanes", "Percentage.of.left.turns", "Average.daily.total.traffic", "Movements",
"Shoulder.width", "Percentage.of.trucks", "Clearance", "Speed.Limit"), fun = c("length",
"mean_rm", "sd_rm", "min_rm", "max_rm"), nr = 8)
safety.table <- result$tab
output$safety.table <- renderTable({
colm <- as.numeric(unlist(input$safety.summary))
safety.table[colm]
}

5. )
# ------------------------- END PANEL 3 --------------------------- #
# ------------------------- START PANEL 4 --------------------------- #
result <- evalreg(dataset = "time.parameter", pred = c("X..of.left.turns",
"Average.Daily.Total.Traffic", "Speed.Limit"), rvar = "Annual.hours.wasted.in.traffic", train =
"All")
# summary(result)
# plot("result")
output$result <- renderPrint({summary(result)})
result.1 <- evalreg(dataset = "safety.parameter", pred =
c("Shoulder.width","Percentage.of.trucks", "Clearance"), rvar = "Average.daily.total.traffic",
train = "All")
output$result.1 <- renderPrint({summary(result.1)})
# ------------------------- END PANEL 4 --------------------------- #
# PLOT FOR TIME AND COST
output$plot1 <- renderPlot({
plot(final.weighted.data$Time.100, final.weighted.data$Cost.100, xlab = "Weighted Time
Results", ylab = "Weighted Cost Results", type = "p")
})
# Verbatim Text Output for COST - TIME
output$info <- renderText({
xy_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0("x=", round(e$x, 4), " y=", round(e$y, 4), "n")
}
xy_range_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0("xmin=", round(e$xmin, 4), " xmax=", round(e$xmax, 4),
" ymin=", round(e$ymin, 4), " ymax=", round(e$ymax, 4))
}
paste0(
"click: ", xy_str(input$plot_click),
"dblclick: ", xy_str(input$plot_dblclick),
"hover: ", xy_str(input$plot_hover),
"brush: ", xy_range_str(input$plot_brush)
)

6. })
# PLOT FOR TIME AND SAFETY
output$plot2 <- renderPlot({
plot(final.weighted.data$Time.100, final.weighted.data$Safety.100, xlab = "Weighted Time
Results", ylab = "Weighted Safety Results", type = "p")
})
# Verbatim Text Output for SAFETY - TIME
output$info1 <- renderText({
xy_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0("x=", round(e$x, 4), " y=", round(e$y, 4), "n")
}
xy_range_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0("xmin=", round(e$xmin, 4), " xmax=", round(e$xmax, 4),
" ymin=", round(e$ymin, 4), " ymax=", round(e$ymax, 4))
}
paste0(
"click: ", xy_str(input$plot_click),
"dblclick: ", xy_str(input$plot_dblclick),
"hover: ", xy_str(input$plot_hover),
"brush: ", xy_range_str(input$plot_brush)
)
})
# PLOT FOR COST AND SAFETY
output$plot3 <- renderPlot({
plot(final.weighted.data$Cost.100, final.weighted.data$Safety.100, xlab = "Weighted Cost
Results", ylab = "Weighted Safety Results", type = "p")
})
# Verbatim Text Output for SAFETY - COST
output$info2 <- renderText({
xy_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0("x=", round(e$x, 4), " y=", round(e$y, 4), "n")
}
xy_range_str <- function(e) {
if(is.null(e)) return("NULLn")
paste0(" xmin=", round(e$xmin, 4), " xmax=", round(e$xmax, 4),
" ymin=", round(e$ymin, 4), " ymax=", round(e$ymax, 4))

7. }
paste0(
"click: ", xy_str(input$plot_click),
"dblclick: ", xy_str(input$plot_dblclick),
"hover: ", xy_str(input$plot_hover),
"brush: ", xy_range_str(input$plot_brush)
)
})
# ---------------------------------------------------------
output$gvis <- renderGvis({ gvisMotionChart(volume.by.year.1, idvar = "Intersection..SB...NB.",
timevar = "Year")
})
output$socialgood <- renderGvis({ gvisMotionChart(social.good.2016, idvar = "Intersections",
timevar = "Year")
})
output$x <- renderGvis({ gvisMap(volume.by.year.1, locationvar = "Location", tipvar =
c("Intersection..SB...NB."), options=list(showTip=TRUE, showLine=TRUE,
enableScrollWheel=TRUE, mapType='normal', useMapTypeControl=TRUE,
width=800,height=400))
})
# ---------------------------------------------------------
threed.plot <- plot_ly(x = volumeByYear2013$One.way.Traffic.Volume.am, y =
volumeByYear2013$One.way.Traffic.Volume.md, z =
volumeByYear2013$One.way.Traffic.Volume.pm, type = "scatter3d", color =
volumeByYear2013$Intersection..SB...NB., colors = "Set1", width = 600, height = 400) %>%
layout(title = "Traffic Comparison by Intersection", scene = list(xaxis = list(title = "Peak AM
Traffic"), yaxis = list(title = "Peak PM Traffic"), zaxis = list(title= "Peak MD Traffic")))
output$plot_ly <- renderPlotly({ threed.plot
})
output$hover_ly <- renderPrint({
d <- event_data("plotly_hover")
if (is.null(d)) "Hover events appear here (unhover to clear)" else d
})
output$click_ly <- renderPrint({

8. d <- event_data("plotly_click")
if (is.null(d)) "Click events appear here (double-click to clear)" else d
})
# ---------------------------------------------------------
# ---------------------------------------------------------
datasetInput <- reactive({
switch(input$dataset,
"Time.Data" = time.parameter,
"Cost.Data" = cost.parameter,
"Safety.Data" = safety.parameter,
"Social.Good" = social.good.2016)
})
output$downloadData <- downloadHandler(
filename = function() { paste(input$dataset, '.csv', sep='') },
content = function(file) {
write.csv(datasetInput(), file)
}
)
# ---------------------------------------------------------
final.weighted.data <- read.csv("Finalweighteddata1.csv")
radius <- final.weighted.data$size*8
color <- colorFactor(c("#00FF00","#FFFF00","#FF0000"),
final.weighted.data$DDI.Requirement)
popus <- paste(sep = "<br/>",
"Intersection:",
final.weighted.data$Intersection,
"Ranking:",
final.weighted.data$Rank,
"Total Score:",
final.weighted.data$Total.100)
output$map <- renderLeaflet({
m <- leaflet(final.weighted.data) %>%
addTiles('http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png', attribution='Map tiles by
<a href="http://stamen.com">Stamen Design</a>, <a
href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a> &mdash; Map data &copy;
<a href="http://www.openstreetmap.org/copyright">OpenStreetMap</a>')
m %>% setView(-96.8, 32.7833333, zoom = 8)

9. m %>% addCircles(lng= ~lng, lat= ~lat , popup=popus, weight = 7, radius=radius, color=
~color(DDI.Requirement), stroke = TRUE, fillOpacity = 0.8)
})
# ---------------------------------------------------------
output$maps.table <- DT::renderDataTable(final.weighted.data.table, filter = 'top', server =
FALSE)
}
)