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VRP_analysis_markdown.Rmd
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---
title: "VRP_analysis"
author: "Dylan Johnson"
date: "10/06/2021"
output: rmarkdown::github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(
fig.path = "README_figs_vrp/"
)
```
## London Packages
```{r libraries, message = FALSE, warning = FALSE}
library(ggplot2)
library(ggpubr)
library(ggthemes)
library(viridis)
library(hrbrthemes)
library(tidyverse)
library(knitr)
opts_chunk$set(dev="png")
```
## Reading Dataframe
```{r readdataframe, echo=FALSE}
setwd("C:/Projects/Research/Vehicle_Routing_Problem")
network_macroscopic <- read.csv("network_macroscopic_vrp.csv")
```
```{r clean}
colnames(network_macroscopic)[1]<-"Scenario"
network_macroscopic$Scenario <- gsub('[[:digit:]]+', '', network_macroscopic$Scenario)
network_macroscopic$Congestion <- c(rep(seq(.8,1,0.05)))
network_macroscopic$Scenario <- c(rep(paste0("BC"), times = 5),
rep(paste0("CL"), times = 5),
rep(paste0("CL(R)"), times = 5),
rep(paste0("PT"), times = 5))
network_macroscopic <- network_macroscopic[, c(1,12,2:11)]
network_macroscopic$Congestion <- as.factor(network_macroscopic$Congestion)
network_macroscopic$Scenario <- as.factor(network_macroscopic$Scenario)
network_macroscopic$Congestion <- fct_rev(network_macroscopic$Congestion)
network_macroscopic$CO2_kg <- network_macroscopic$emissions_CO2_abs/1000000
network_macroscopic$CO_kg <- network_macroscopic$emissions_CO_abs/1000000
network_macroscopic$HC_kg <- network_macroscopic$emissions_HC_abs/1000000
network_macroscopic$NOx_kg <- network_macroscopic$emissions_NOx_abs/1000000
network_macroscopic$PMx_kg <- network_macroscopic$emissions_PMx_abs/1000000
```
```{r C02_vrp}
co2_vrp <- ggplot(network_macroscopic, aes(x = Scenario, y = CO2_kg, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('CO'[2]*' Emissions (kg)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Network \nCongestion")) +
scale_x_discrete(limits = c("CL(R)", "BC", "CL", "PT"))
co2_vrp
```
## Hydrocarbon
```{r hydrocarbon_vrp}
HC_vrp <- ggplot(network_macroscopic, aes(x = Scenario, y = HC_kg, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('HC Emissions (kg)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Congestion")) +
scale_x_discrete(limits = c( "BC", "CL(R)", "CL", "PT"))
HC_vrp
```
## Nitrogen Oxide
```{r NOx_vrp}
NOx_vrp <- ggplot(network_macroscopic, aes(x = Scenario, y = NOx_kg, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('NOx Emissions (kg)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Congestion")) +
scale_x_discrete(limits = c( "BC", "CL(R)", "CL", "PT"))
NOx_vrp
```
##Particulate Matter
```{r Particulate Matter}
PMx <- ggplot(network_macroscopic, aes(x = Scenario, y = PMx_kg, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('PMx Emissions (kg)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Congestion")) +
scale_x_discrete(limits = c( "BC", "CL(R)", "CL", "PT"))
PMx
```
############################################################## Network Effects ##############################################################
##### Duration
```{r clean duration}
network_macroscopic$duration_hr <- network_macroscopic$tripinfo_duration/3600
network_macroscopic$timeLoss_hr <- network_macroscopic$tripinfo_timeLoss/3600
network_macroscopic$waitingTime_hr <- network_macroscopic$tripinfo_waitingTime/3600
```
```{r duration_vrp}
Duration <- ggplot(network_macroscopic, aes(x = Scenario, y = duration_hr, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('Total Network Trip Time (hr)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Network \n Congestion")) +
scale_x_discrete(limits = c("CL(R)","CL","BC","PT"))
Duration
```
######## Time Loss
```{r time_loss_vrp}
Time_loss <- ggplot(network_macroscopic, aes(x = Scenario, y = timeLoss_hr, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('Total Network Time Loss (hr)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Congestion")) +
scale_x_discrete(limits = c("CL(R)","CL","BC","PT"))
Time_loss
```
######## Waiting_Time
```{r waiting_vrp_time}
Waiting_time <- ggplot(network_macroscopic, aes(x = Scenario, y = waitingTime_hr, colour = Congestion, group = Congestion)) +
geom_line(size=1, linetype=3) +
scale_colour_viridis(discrete = TRUE)+
geom_point(size=3) +
theme_bw() +
xlab("Scenario") +
ylab(expression('Total Network Wait Time (hr)') ) +
theme(axis.title.x=element_text(size=12)) +
theme(axis.text.x=element_text(size=10, face = "bold")) +
theme(axis.title.y=element_text(size=12, face = "bold")) +
theme(axis.text.y=element_text(size=10, face = "bold")) +
theme(legend.title=element_text(size=10, face= "bold"))+
theme(legend.text=element_text(size=8, face = "bold")) +
guides(fill=guide_legend(title= "Congestion")) +
scale_x_discrete(limits = c("CL(R)","CL","BC","PT"))
Waiting_time
```