ndsbr

The goal of ndsbr is to help you load, manipulate and analyze the data sample of the Brazilian Naturalistic Driving Study (NDS-BR).

Overview

This package privides two main categories of functions: nds_create and nds_calc, in addition to other utility functions. nds_create functions are used to create spatial objects in sf format, using the naturalistic data as input:

• nds_create_points
• nds_create_lines

nds_calc functions can be used to extract basic information of the naturalistic sample (traveled time or traveled distance) and safety-related variables, such as speeding:

• nds_calc_dist
• nds_calc_time
• nds_calc_speeding

nds_load_data is used to load naturalistic data and nds_download_sf can be used to download spatial data and import into the project environment.

A brief presentation (in portuguese) about ndsbr can be accessed here.

Installation

You can install the current version of ndsbr like so:

# install.packages("devtools")
devtools::install_github("pabsantos/ndsbr")

Example

This is a basic example which shows you how to load NDS-BR data and calculate traveled distances. First, nds_load_data loads the sample from all NDS-BR files inside a specific folder, defined by the user.

library(ndsbr)
path <- system.file("extdata", package = "ndsbr") ## Example files location
nds_data <- nds_load_data("driver", path)

head(nds_data, n = 5)
#> # A tibble: 5 × 34
#>   DRIVER  LONG   LAT DAY     DAY_C…¹ 03:00…²  TRIP ID    PR        H     M     S
#>   <chr>  <dbl> <dbl> <chr>   <chr>   <chr>   <dbl> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 A      -49.2 -25.5 26/8/2… 26/8/2… 22:17:…     5 A05   19:1…    NA    NA    NA
#> 2 A      -49.2 -25.5 26/8/2… 26/8/2… 22:17:…     5 A05   19:1…     0     0     1
#> 3 A      -49.2 -25.5 26/8/2… 26/8/2… 22:17:…     5 A05   19:1…     0     0     1
#> 4 A      -49.2 -25.5 26/8/2… 26/8/2… 22:17:…     5 A05   19:1…     0     0     1
#> 5 A      -49.2 -25.5 26/8/2… 26/8/2… 22:17:…     5 A05   19:1…     0     0     1
#> # … with 22 more variables: TIME_ACUM <dbl>, SPD_MPH <dbl>, SPD_KMH <dbl>,
#> #   ACEL_MS2 <dbl>, HEADING <dbl>, ALTITUDE_FT <dbl>, VALID_TIME <chr>,
#> #   TIMESTAMP_GPS <chr>, CPOOL <chr>, CPOOLING_CHECKED <chr>, WSB <chr>,
#> #   UMP_YN <chr>, UMP <chr>, PICK_UP <chr>, ACTION <chr>, GPS_FILE <chr>,
#> #   CIDADE <chr>, BAIRRO <chr>, NOME_RUA <chr>, HIERARQUIA_CWB <chr>,
#> #   HIERARQUIA_CTB <chr>, LIMITE_VEL <chr>, and abbreviated variable names
#> #   ¹​DAY_CORRIGIDO, ²​`03:00:00`

Creating a sf object with linestring geometry using nds_create_lines

nds_lines <- nds_create_lines(nds_data, x = LONG, y = LAT)

plot(nds_lines["DRIVER"])

Finally, nds_calc_dist extracts traveled distance, grouped by a variable defined by the user.

nds_dist <- nds_calc_dist(nds_lines, geom = wkt_lines, by = DRIVER)
nds_dist
#> # A tibble: 3 × 2
#>   DRIVER   DIST
#>   <chr>   <dbl>
#> 1 A      22508.
#> 2 B      51529.
#> 3 C      37736.