This document loads various libraries and reads in multiple csv files containing transportation data. It then performs some data cleaning and preprocessing steps. Various outputs are defined to render tables and plots of subsets of the data. Plots are created to visualize relationships between weighted time, cost, and safety metrics. Interactive elements are added to output text describing user input from the plots. Maps and motion charts are also defined as outputs to visualize additional data aspects.

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)
}
)