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Calculate access to opportunities

Source: R/accessibility.R
accessibility.Rd

Fast computation of access to opportunities given a selected decay function.

Usage

accessibility(
  r5r_core,
  origins,
  destinations,
  opportunities_colnames = "opportunities",
  mode = "WALK",
  mode_egress = "WALK",
  departure_datetime = Sys.time(),
  time_window = 10L,
  percentiles = 50L,
  decay_function = "step",
  cutoffs = NULL,
  decay_value = NULL,
  fare_structure = NULL,
  max_fare = Inf,
  max_walk_time = Inf,
  max_bike_time = Inf,
  max_car_time = Inf,
  max_trip_duration = 120L,
  walk_speed = 3.6,
  bike_speed = 12,
  max_rides = 3,
  max_lts = 2,
  draws_per_minute = 5L,
  n_threads = Inf,
  verbose = FALSE,
  progress = FALSE,
  output_dir = NULL
)

Arguments

r5r_core

An object to connect with the R5 routing engine, created with setup_r5().

origins, destinations

Either a POINT sf object with WGS84 CRS, or a data.frame containing the columns id, lon and lat.

opportunities_colnames

A character vector. The names of the columns in the destinations input that tells the number of opportunities in each location. Several different column names can be passed, in which case the accessibility to each kind of opportunity will be calculated.

mode

A character vector. The transport modes allowed for access, transfer and vehicle legs of the trips. Defaults to WALK. Please see details for other options.

mode_egress

A character vector. The transport mode used after egress from the last public transport. It can be either WALK, BICYCLE or CAR. Defaults to WALK. Ignored when public transport is not used.

departure_datetime

A POSIXct object. Please note that the departure time only influences public transport legs. When working with public transport networks, please check the calendar.txt within your GTFS feeds for valid dates. Please see details for further information on how datetimes are parsed.

time_window

An integer. The time window in minutes for which r5r will calculate multiple travel time matrices departing each minute. Defaults to 10 minutes. By default, the function returns the result based on median travel times, but the user can set the percentiles parameter to extract more results. Please read the time window vignette for more details on its usage vignette("time_window", package = "r5r")

percentiles

An integer vector (max length of 5). Specifies the percentile to use when returning accessibility estimates within the given time window. Please note that this parameter is applied to the travel time estimates that generate the accessibility results, and not to the accessibility distribution itself (i.e. if the 25th percentile is specified, the accessibility is calculated from the 25th percentile travel time, which may or may not be equal to the 25th percentile of the accessibility distribution itself). Defaults to 50, returning the accessibility calculated from the median travel time. If a vector with length bigger than 1 is passed, the output contains an additional column that specifies the percentile of each accessibility estimate. Due to upstream restrictions, only 5 percentiles can be specified at a time. For more details, please see R5 documentation at https://docs.conveyal.com/analysis/methodology#accounting-for-variability.

decay_function

A string. Which decay function to use when calculating accessibility. One of step, exponential, fixed_exponential, linear or logistic. Defaults to step, which is equivalent to a cumulative opportunities measure. Please see the details to understand how each alternative works and how they relate to the cutoffs and decay_value parameters.

cutoffs

A numeric vector (maximum length of 12). This parameter has different effects for each decay function: it indicates the cutoff times in minutes when calculating cumulative opportunities accessibility with the step function, the median (or inflection point) of the decay curves in the logistic and linear functions, and the half-life in the exponential function. It has no effect when using the fixed_exponential function.

decay_value

A number. Extra parameter to be passed to the selected decay_function. Has no effects when decay_function is either step or exponential.

fare_structure

A fare structure object, following the convention set in setup_fare_structure(). This object describes how transit fares should be calculated. Please see the fare structure vignette to understand how this object is structured: vignette("fare_structure", package = "r5r").

max_fare

A number. The maximum value that trips can cost when calculating the fastest journey between each origin and destination pair.

max_walk_time

An integer. The maximum walking time (in minutes) to access and egress the transit network, to make transfers within the network or to complete walk-only trips. Defaults to no restrictions (numeric value of Inf), as long as max_trip_duration is respected. When routing transit trips, the max time is considered separately for each leg (e.g. if you set max_walk_time to 15, you could get trips with an up to 15 minutes walk leg to reach transit and another up to 15 minutes walk leg to reach the destination after leaving transit. In walk-only trips, whenever max_walk_time differs from max_trip_duration, the lowest value is considered.

max_bike_time

An integer. The maximum cycling time (in minutes) to access and egress the transit network, to make transfers within the network or to complete bicycle-only trips. Defaults to no restrictions (numeric value of Inf), as long as max_trip_duration is respected. When routing transit trips, the max time is considered separately for each leg (e.g. if you set max_bike_time to 15, you could get trips with an up to 15 minutes cycle leg to reach transit and another up to 15 minutes cycle leg to reach the destination after leaving transit. In bicycle-only trips, whenever max_bike_time differs from max_trip_duration, the lowest value is considered.

max_car_time

An integer. The maximum driving time (in minutes) to access and egress the transit network. Defaults to no restrictions, as long as max_trip_duration is respected. The max time is considered separately for each leg (e.g. if you set max_car_time to 15 minutes, you could potentially drive up to 15 minutes to reach transit, and up to another 15 minutes to reach the destination after leaving transit). Defaults to Inf, no limit.

max_trip_duration

An integer. The maximum trip duration in minutes. Defaults to 120 minutes (2 hours).

walk_speed

A numeric. Average walk speed in km/h. Defaults to 3.6 km/h.

bike_speed

A numeric. Average cycling speed in km/h. Defaults to 12 km/h.

max_rides

An integer. The maximum number of public transport rides allowed in the same trip. Defaults to 3.

max_lts

An integer between 1 and 4. The maximum level of traffic stress that cyclists will tolerate. A value of 1 means cyclists will only travel through the quietest streets, while a value of 4 indicates cyclists can travel through any road. Defaults to 2. Please see details for more information.

draws_per_minute

An integer. The number of Monte Carlo draws to perform per time window minute when calculating travel time matrices and when estimating accessibility. Defaults to 5. This would mean 300 draws in a 60-minute time window, for example. This parameter only affects the results when the GTFS feeds contain a frequencies.txt table.

n_threads

An integer. The number of threads to use when running the router in parallel. Defaults to use all available threads (Inf).

verbose

A logical. Whether to show R5 informative messages when running the function. Defaults to FALSE (please note that in such case R5 error messages are still shown). Setting verbose to TRUE shows detailed output, which can be useful for debugging issues not caught by r5r.

progress

A logical. Whether to show a progress counter when running the router. Defaults to FALSE. Only works when verbose is set to FALSE, so the progress counter does not interfere with R5's output messages. Setting progress to TRUE may impose a small penalty for computation efficiency, because the progress counter must be synchronized among all active threads.

output_dir

Either NULL or a path to an existing directory. When not NULL (the default), the function will write one .csv file with the results for each origin in the specified directory. In such case, the function returns the path specified in this parameter. This parameter is particularly useful when running on memory-constrained settings because writing the results directly to disk prevents r5r from loading them to RAM memory.

Value

A data.table with accessibility estimates for all origin points. This data.table contain columns listing the origin id, the type of opportunities to which accessibility was calculated, the travel time percentile considered in the accessibility estimate and the specified cutoff values (except in when decay_function is fixed_exponential, in which case the cutoff parameter is not used). If output_dir is not NULL, the function returns the path specified in that parameter, in which the .csv files containing the results are saved.

Decay functions

R5 allows one to use different decay functions when calculating accessibility. Please see the original R5 documentation from Conveyal for more information on each one one (https://docs.conveyal.com/learn-more/decay-functions). A summary of each available option, as well as the value passed to decay_function to use it (inside parentheses) are listed below:

  • Step, also known as cumulative opportunities ("step"):
    a binary decay function used to find the sum of available opportunities within a specific travel time cutoff.

  • Logistic CDF ("logistic"):
    This is the logistic function, i.e. the cumulative distribution function of the logistic distribution, expressed such that its parameters are the median (inflection point) and standard deviation. This function applies a sigmoid rolloff that has a convenient relationship to discrete choice theory. Its parameters can be set to reflect a whole population's tolerance for making trips with different travel times. The function's value represents the probability that a randomly chosen member of the population would accept making a trip, given its duration. Opportunities are then weighted by how likely it is that a person would consider them "reachable".

    • Calibration: The median parameter is controlled by the cutoff parameter, leaving only the standard deviation to configure through the decay_value parameter.

  • Fixed Exponential ("fixed_exponential"):
    This function is of the form exp(-Lt) where L is a single fixed decay constant in the range (0, 1). It is constrained to be positive to ensure weights decrease (rather than grow) with increasing travel time.

    • Calibration: This function is controlled exclusively by the L constant, given by the decay_value parameter. Values provided in cutoffs are ignored.

  • Half-life Exponential Decay ("exponential"):
    This is similar to the fixed-exponential option above, but in this case the decay parameter is inferred from the cutoffs parameter values, which is treated as the half-life of the decay.

  • Linear ("linear"):
    This is a simple, vaguely sigmoid option, which may be useful when you have a sense of a maximum travel time that would be tolerated by any traveler, and a minimum time below which all travel is perceived to be equally easy.

    • Calibration: The transition region is transposable and symmetric around the cutoffs parameter values, taking decay_value minutes to taper down from one to zero.

Transport modes

R5 allows for multiple combinations of transport modes. The options include:

  • Transit modes: TRAM, SUBWAY, RAIL, BUS, FERRY, CABLE_CAR, GONDOLA, FUNICULAR. The option TRANSIT automatically considers all public transport modes available.

  • Non transit modes: WALK, BICYCLE, CAR, BICYCLE_RENT, CAR_PARK.

Level of Traffic Stress (LTS)

When cycling is enabled in R5 (by passing the value BIKE to either mode or mode_egress), setting max_lts will allow cycling only on streets with a given level of danger/stress. Setting max_lts to 1, for example, will allow cycling only on separated bicycle infrastructure or low-traffic streets and routing will revert to walking when traversing any links with LTS exceeding 1. Setting max_lts to 3 will allow cycling on links with LTS 1, 2 or 3. Routing also reverts to walking if the street segment is tagged as non-bikable in OSM (e.g. a staircase), independently of the specified max LTS.

The default methodology for assigning LTS values to network edges is based on commonly tagged attributes of OSM ways. See more info about LTS in the original documentation of R5 from Conveyal at https://docs.conveyal.com/learn-more/traffic-stress. In summary:

  • LTS 1: Tolerable for children. This includes low-speed, low-volume streets, as well as those with separated bicycle facilities (such as parking-protected lanes or cycle tracks).

  • LTS 2: Tolerable for the mainstream adult population. This includes streets where cyclists have dedicated lanes and only have to interact with traffic at formal crossing.

  • LTS 3: Tolerable for "enthused and confident" cyclists. This includes streets which may involve close proximity to moderate- or high-speed vehicular traffic.

  • LTS 4: Tolerable only for "strong and fearless" cyclists. This includes streets where cyclists are required to mix with moderate- to high-speed vehicular traffic.

For advanced users, you can provide custom LTS values by adding a tag <key = "lts"> to the osm.pbf file.

Datetime parsing

r5r ignores the timezone attribute of datetime objects when parsing dates and times, using the study area's timezone instead. For example, let's say you are running some calculations using Rio de Janeiro, Brazil, as your study area. The datetime as.POSIXct("13-05-2019 14:00:00", format = "%d-%m-%Y %H:%M:%S") will be parsed as May 13th, 2019, 14:00h in Rio's local time, as expected. But as.POSIXct("13-05-2019 14:00:00", format = "%d-%m-%Y %H:%M:%S", tz = "Europe/Paris") will also be parsed as the exact same date and time in Rio's local time, perhaps surprisingly, ignoring the timezone attribute.

Routing algorithm

The travel_time_matrix(), expanded_travel_time_matrix() and accessibility() functions use an R5-specific extension to the RAPTOR routing algorithm (see Conway et al., 2017). This RAPTOR extension uses a systematic sample of one departure per minute over the time window set by the user in the 'time_window' parameter. A detailed description of base RAPTOR can be found in Delling et al (2015). However, whenever the user includes transit fares inputs to these functions, they automatically switch to use an R5-specific extension to the McRAPTOR routing algorithm.

  • Conway, M. W., Byrd, A., & van der Linden, M. (2017). Evidence-based transit and land use sketch planning using interactive accessibility methods on combined schedule and headway-based networks. Transportation Research Record, 2653(1), 45-53. doi:10.3141/2653-06

  • Delling, D., Pajor, T., & Werneck, R. F. (2015). Round-based public transit routing. Transportation Science, 49(3), 591-604. doi:10.1287/trsc.2014.0534

Examples

library(r5r)

data_path <- system.file("extdata/poa", package = "r5r")
r5r_core <- setup_r5(data_path)
#> Using cached R5 version from /home/runner/.cache/R/r5r/r5_jar_v7.1.0/r5-v7.1-all.jar
#> 
#> Using cached network.dat from /home/runner/work/_temp/Library/r5r/extdata/poa/network.dat
points <- read.csv(file.path(data_path, "poa_hexgrid.csv"))[1:5, ]

departure_datetime <- as.POSIXct(
  "13-05-2019 14:00:00",
  format = "%d-%m-%Y %H:%M:%S"
)

access <- accessibility(
  r5r_core,
  origins = points,
  destinations = points,
  opportunities_colnames = "schools",
  mode = "WALK",
  departure_datetime = departure_datetime,
  decay_function = "step",
  cutoffs = 30,
  max_trip_duration = 30
)
head(access)
#>                 id opportunity percentile cutoff accessibility
#>             <char>      <char>      <int>  <int>         <num>
#> 1: 89a901291abffff     schools         50     30             0
#> 2: 89a9012a3cfffff     schools         50     30             0
#> 3: 89a901295b7ffff     schools         50     30             0
#> 4: 89a901284a3ffff     schools         50     30             0
#> 5: 89a9012809bffff     schools         50     30             0

# using a different decay function
access <- accessibility(
  r5r_core,
  origins = points,
  destinations = points,
  opportunities_colnames = "schools",
  mode = "WALK",
  departure_datetime = departure_datetime,
  decay_function = "logistic",
  cutoffs = 30,
  decay_value = 1,
  max_trip_duration = 30
)
head(access)
#>                 id opportunity percentile cutoff accessibility
#>             <char>      <char>      <int>  <int>         <num>
#> 1: 89a901291abffff     schools         50     30             0
#> 2: 89a9012a3cfffff     schools         50     30             0
#> 3: 89a901295b7ffff     schools         50     30             0
#> 4: 89a901284a3ffff     schools         50     30             0
#> 5: 89a9012809bffff     schools         50     30             0

# using several cutoff values
access <- accessibility(
  r5r_core,
  origins = points,
  destinations = points,
  opportunities_colnames = "schools",
  mode = "WALK",
  departure_datetime = departure_datetime,
  decay_function = "step",
  cutoffs = c(25, 30),
  max_trip_duration = 30
)
head(access)
#>                 id opportunity percentile cutoff accessibility
#>             <char>      <char>      <int>  <int>         <num>
#> 1: 89a901291abffff     schools         50     25             0
#> 2: 89a901291abffff     schools         50     30             0
#> 3: 89a9012a3cfffff     schools         50     25             0
#> 4: 89a9012a3cfffff     schools         50     30             0
#> 5: 89a901295b7ffff     schools         50     25             0
#> 6: 89a901295b7ffff     schools         50     30             0

# calculating access to different types of opportunities
access <- accessibility(
  r5r_core,
  origins = points,
  destinations = points,
  opportunities_colnames = c("schools", "healthcare"),
  mode = "WALK",
  departure_datetime = departure_datetime,
  decay_function = "step",
  cutoffs = 30,
  max_trip_duration = 30
)
head(access)
#>                 id opportunity percentile cutoff accessibility
#>             <char>      <char>      <int>  <int>         <num>
#> 1: 89a901291abffff     schools         50     30             0
#> 2: 89a901291abffff  healthcare         50     30             0
#> 3: 89a9012a3cfffff     schools         50     30             0
#> 4: 89a9012a3cfffff  healthcare         50     30             0
#> 5: 89a901295b7ffff     schools         50     30             0
#> 6: 89a901295b7ffff  healthcare         50     30             1

stop_r5(r5r_core)
#> r5r_core has been successfully stopped.