Carlsbad-Blvd
setwd("C:/Users/s-das/Syncplicity Folders/MY_Projects/NCHRP 17-76/04102017/Data Sources/INRIX/")
a01 <- read.csv("C/Carlsbad-Blvd-entire-length-9-11-16.csv")
str(a01)
## 'data.frame': 108864 obs. of 9 variables:
## $ tmc_code : Factor w/ 54 levels "106-13652","106-13653",..: 3 41 49 10 45 40 27 47 36 42 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : num 21 25 22 30 22 35 32 44 40 33 ...
## $ average_speed : int 21 25 22 30 22 35 32 44 40 33 ...
## $ reference_speed : int 20 22 16 29 31 31 32 40 36 34 ...
## $ travel_time_minutes: num 1.3 0.04 0.04 1.6 0.13 0.01 3.74 0.28 0.5 0.03 ...
## $ confidence_score : num 20 20 20 20 20 20 20 20 20 20 ...
## $ cvalue : num 0 0 0 0 0 0 0 0 0 0 ...
## $ tmc1 : Factor w/ 54 levels "TMC106-13652",..: 3 41 49 10 45 40 27 47 36 42 ...
a02 <- read.csv("C/TMC_Identification1.csv")
a03 <- merge(a01, a02, by="tmc1")
dim(a01)
## [1] 108864 9
dim(a02)
## [1] 54 14
dim(a03)
## [1] 108864 22
names(a03)
## [1] "tmc1" "tmc_code" "measurement_tstamp"
## [4] "speed" "average_speed" "reference_speed"
## [7] "travel_time_minutes" "confidence_score" "cvalue"
## [10] "tmc" "road" "direction"
## [13] "intersection" "state" "county"
## [16] "zip" "start_latitude" "start_longitude"
## [19] "end_latitude" "end_longitude" "miles"
## [22] "road_order"
table(a03$direction)
##
## NORTHBOUND SOUTHBOUND
## 54432 54432
library(lubridate)
##
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
##
## date
a03$Time <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%H:%M")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date <- format(as.POSIXct(strptime(a03$measurement_tstamp, "%m/%d/%Y %H:%M",tz="")) ,format = "%Y-%m-%d")
a03$Time1 <- as.POSIXct(a03$Time, format = "%H:%M")
a03$Date1 <- as.Date(a03$Date)
a03$Day <- wday(a03$Date1, label = TRUE)
str(a03)
## 'data.frame': 108864 obs. of 27 variables:
## $ tmc1 : Factor w/ 54 levels "TMC106-13652",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ tmc_code : Factor w/ 54 levels "106-13652","106-13653",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ measurement_tstamp : Factor w/ 2016 levels "9/11/2016 0:00",..: 1515 1238 1355 1036 1893 371 1257 18 45 1460 ...
## $ speed : num 14 24.2 27 27.2 27 ...
## $ average_speed : int 21 21 27 28 26 24 22 28 22 25 ...
## $ reference_speed : int 28 28 28 28 28 28 28 28 28 28 ...
## $ travel_time_minutes: num 4.17 2.42 2.16 2.15 2.16 2.26 2.65 2.08 2.94 2.33 ...
## $ confidence_score : num 30 30 20 28 30 30 20 20 30 20 ...
## $ cvalue : num 63.4 100 0 80 100 100 0 0 100 0 ...
## $ tmc : Factor w/ 54 levels "106-13652","106-13653",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ road : Factor w/ 1 level "CR-S21": 1 1 1 1 1 1 1 1 1 1 ...
## $ direction : Factor w/ 2 levels "NORTHBOUND","SOUTHBOUND": 2 2 2 2 2 2 2 2 2 2 ...
## $ intersection : Factor w/ 18 levels "4TH ST/DEL MAR HEIGHTS RD",..: 17 17 17 17 17 17 17 17 17 17 ...
## $ state : Factor w/ 1 level "CA": 1 1 1 1 1 1 1 1 1 1 ...
## $ county : Factor w/ 1 level "SAN DIEGO": 1 1 1 1 1 1 1 1 1 1 ...
## $ zip : int 92054 92054 92054 92054 92054 92054 92054 92054 92054 92054 ...
## $ start_latitude : num 33.2 33.2 33.2 33.2 33.2 ...
## $ start_longitude : num -117 -117 -117 -117 -117 ...
## $ end_latitude : num 33.2 33.2 33.2 33.2 33.2 ...
## $ end_longitude : num -117 -117 -117 -117 -117 ...
## $ miles : num 0.973 0.973 0.973 0.973 0.973 ...
## $ road_order : num 7 7 7 7 7 7 7 7 7 7 ...
## $ Time : chr "14:10" "15:05" "23:50" "21:15" ...
## $ Time1 : POSIXct, format: "2017-04-13 14:10:00" "2017-04-13 15:05:00" ...
## $ Date : chr "2016-09-16" "2016-09-15" "2016-09-15" "2016-09-14" ...
## $ Date1 : Date, format: "2016-09-16" "2016-09-15" ...
## $ Day : Ord.factor w/ 7 levels "Sun"<"Mon"<"Tues"<..: 6 5 5 4 7 2 5 1 1 6 ...
aa1 <- subset(a03, direction=="NORTHBOUND")
aa3 <- subset(a03, direction=="SOUTHBOUND")
require(ggplot2)
## Loading required package: ggplot2
require(scales)
## Loading required package: scales
ggplot(aa1, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Northbound)")
ggplot(aa1, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Northbound)")
ggplot(aa3, aes(x=Time1, y=speed)) +
geom_point(size=.9, alpha = 0.05, colour="green") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Southbound)")
ggplot(aa3, aes(x=Time1, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)", title=
"Carlsbad Blvd (Southbound)")
aa2 <- aggregate(speed ~ Time1+direction+Day, a03, mean)
head(aa2)
## Time1 direction Day speed
## 1 2017-04-13 00:00:00 NORTHBOUND Sun 31.36963
## 2 2017-04-13 00:05:00 NORTHBOUND Sun 31.30259
## 3 2017-04-13 00:10:00 NORTHBOUND Sun 31.27370
## 4 2017-04-13 00:15:00 NORTHBOUND Sun 31.31037
## 5 2017-04-13 00:20:00 NORTHBOUND Sun 31.44444
## 6 2017-04-13 00:25:00 NORTHBOUND Sun 31.37481
dim(aa1)
## [1] 54432 27
dim(aa2)
## [1] 4032 4
colnames(aa2)[2] <- "Direction"
ggplot(aa2, aes(x=Time1, y=speed, colour=Direction)) +
geom_path() + geom_point(cex=0.4)+
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
NPMRDS
setwd("F:/NPMRDS/112016/FHWA_TASK2-4_US_11_2016_TT")
ga <- read.csv("GA_Forsyth.csv")
ga$DATE <- format(as.POSIXct(strptime(as.character(ga$DATE), "%m/%d/%Y",tz="")) ,format = "%Y-%m-%d")
ga$Time2 <- as.POSIXct(ga$Time, format = "%H:%M")
str(ga)
## 'data.frame': 34547 obs. of 19 variables:
## $ TMC : Factor w/ 6 levels "101N04224","101N04225",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ DATE : chr "2016-11-01" "2016-11-01" "2016-11-01" "2016-11-01" ...
## $ EPOCH : int 5 7 8 9 12 13 14 16 17 20 ...
## $ Min : int 30 40 45 50 65 70 75 85 90 105 ...
## $ Travel_TIME_ALL_VEHICLES : int 240 265 245 257 301 256 214 279 235 216 ...
## $ Travel_TIME_PASSENGER_VEHICLES: int 240 NA 245 257 301 256 NA 279 235 NA ...
## $ Travel_TIME_FREIGHT_TRUCKS : int NA 265 NA NA NA NA 214 NA NA 216 ...
## $ Time : Factor w/ 288 levels "0:00","0:05",..: 7 9 10 11 14 15 16 18 19 22 ...
## $ ADMIN_LEVEL_1 : Factor w/ 1 level "USA": 1 1 1 1 1 1 1 1 1 1 ...
## $ ADMIN_LEVEL_2 : Factor w/ 1 level "Georgia": 1 1 1 1 1 1 1 1 1 1 ...
## $ ADMIN_LEVEL_3 : Factor w/ 1 level "Forsyth": 1 1 1 1 1 1 1 1 1 1 ...
## $ DISTANCE : num 4.18 4.18 4.18 4.18 4.18 ...
## $ ROAD_NUMBER : Factor w/ 1 level "US-19": 1 1 1 1 1 1 1 1 1 1 ...
## $ ROAD_NAME : logi NA NA NA NA NA NA ...
## $ LATITUDE : num 34.1 34.1 34.1 34.1 34.1 ...
## $ LONGITUDE : num -84.2 -84.2 -84.2 -84.2 -84.2 ...
## $ ROAD_DIRECTION : Factor w/ 1 level "Southbound": 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : int 63 57 61 59 50 59 70 54 64 70 ...
## $ Time2 : POSIXct, format: "2017-04-13 00:30:00" "2017-04-13 00:40:00" ...
library(lubridate)
ga$Date1 <- as.Date(ga$DATE)
ga$Day <- wday(ga$DATE, label=TRUE)
str(ga)
## 'data.frame': 34547 obs. of 21 variables:
## $ TMC : Factor w/ 6 levels "101N04224","101N04225",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ DATE : chr "2016-11-01" "2016-11-01" "2016-11-01" "2016-11-01" ...
## $ EPOCH : int 5 7 8 9 12 13 14 16 17 20 ...
## $ Min : int 30 40 45 50 65 70 75 85 90 105 ...
## $ Travel_TIME_ALL_VEHICLES : int 240 265 245 257 301 256 214 279 235 216 ...
## $ Travel_TIME_PASSENGER_VEHICLES: int 240 NA 245 257 301 256 NA 279 235 NA ...
## $ Travel_TIME_FREIGHT_TRUCKS : int NA 265 NA NA NA NA 214 NA NA 216 ...
## $ Time : Factor w/ 288 levels "0:00","0:05",..: 7 9 10 11 14 15 16 18 19 22 ...
## $ ADMIN_LEVEL_1 : Factor w/ 1 level "USA": 1 1 1 1 1 1 1 1 1 1 ...
## $ ADMIN_LEVEL_2 : Factor w/ 1 level "Georgia": 1 1 1 1 1 1 1 1 1 1 ...
## $ ADMIN_LEVEL_3 : Factor w/ 1 level "Forsyth": 1 1 1 1 1 1 1 1 1 1 ...
## $ DISTANCE : num 4.18 4.18 4.18 4.18 4.18 ...
## $ ROAD_NUMBER : Factor w/ 1 level "US-19": 1 1 1 1 1 1 1 1 1 1 ...
## $ ROAD_NAME : logi NA NA NA NA NA NA ...
## $ LATITUDE : num 34.1 34.1 34.1 34.1 34.1 ...
## $ LONGITUDE : num -84.2 -84.2 -84.2 -84.2 -84.2 ...
## $ ROAD_DIRECTION : Factor w/ 1 level "Southbound": 1 1 1 1 1 1 1 1 1 1 ...
## $ speed : int 63 57 61 59 50 59 70 54 64 70 ...
## $ Time2 : POSIXct, format: "2017-04-13 00:30:00" "2017-04-13 00:40:00" ...
## $ Date1 : Date, format: "2016-11-01" "2016-11-01" ...
## $ Day : Ord.factor w/ 7 levels "Sun"<"Mon"<"Tues"<..: 3 3 3 3 3 3 3 3 3 3 ...
library(ggplot2)
library(scales)
ggplot(ga, aes(x=Time2, y=speed)) +
geom_point(size=1.1, alpha = 0.05, colour="blue") +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M"))+theme_bw()+labs(x="Time of Day", y="Speed (mph)")
ggplot(ga, aes(x=Time2, y=speed, colour=Day)) +
geom_point(cex=0.6) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
ggplot(ga, aes(x=Time2, y=speed, colour=Day)) +
geom_point(size=.5, alpha = 0.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
aa2 <- aggregate(speed ~ Time2 + Day, ga, mean)
head(aa2)
## Time2 Day speed
## 1 2017-04-13 00:00:00 Sun 62.00000
## 2 2017-04-13 00:05:00 Sun 59.00000
## 3 2017-04-13 00:10:00 Sun 55.80000
## 4 2017-04-13 00:15:00 Sun 56.00000
## 5 2017-04-13 00:20:00 Sun 56.80000
## 6 2017-04-13 00:25:00 Sun 56.57143
ggplot(aa2, aes(x=Time2, speed, colour=Day)) +
geom_path(cex=1.1) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +
facet_grid(Day ~.) +
theme(legend.position="none") +theme_bw()+labs(x="Time of Day", y="Speed (mph)")
ggplot(aa2, aes(x=Time2, y=speed, colour=Day)) +
geom_path(cex=0.8) +
scale_x_datetime(breaks=date_breaks("2 hour"), labels=date_format("%H:%M")) +theme_bw()+
labs(x="Time of Day", y="Speed (mph)")
