Calculate travel times from one stop to all reachable stops

Source: R/raptor.R

raptor finds the minimal travel time, earliest or latest arrival time for all stops in stop_times with journeys departing from stop_ids within time_range.

raptor(
  stop_times,
  transfers,
  stop_ids,
  arrival = FALSE,
  time_range = 3600,
  max_transfers = NULL,
  keep = "all"
)

Arguments

stop_times

A (prepared) stop_times table from a gtfs feed. Prepared means that all stop time rows before the desired journey departure time should be removed. The table should also only include departures happening on one day. Use filter_stop_times() for easier preparation.

transfers

Transfers table from a gtfs feed. In general no preparation is needed. Can be omitted if stop_times has been prepared with filter_stop_times().

stop_ids

Character vector with stop_ids from where journeys should start (or end). It is recommended to only use stop_ids that are related to each other, like different platforms in a train station or bus stops that are reasonably close to each other.

arrival

If FALSE (default), all journeys start from stop_ids. If TRUE, all journeys end at stop_ids.

time_range

Either a range in seconds or a vector containing the minimal and maximal departure time (i.e. earliest and latest possible journey departure time) as seconds or "HH:MM:SS" character. If arrival is TRUE, time_range describes the time window when journeys should end at stop_ids.

max_transfers

Maximum number of transfers allowed, no limit (NULL) as default.

keep

One of c("all", "shortest", "earliest", "latest"). By default, all journeys between stop_ids are returned. With shortest only the journey with the shortest travel time is returned. With earliest the journey arriving at a stop the earliest is returned, latest works accordingly.

Value

A data.table with journeys (departure, arrival and travel time) to/from all stop_ids reachable by stop_ids.

Details

With a modified Round-Based Public Transit Routing Algorithm (RAPTOR) using data.table, earliest arrival times for all stops are calculated. If two journeys arrive at the same time, the one with the later departure time and thus shorter travel time is kept. By default, all journeys departing within time_range that arrive at a stop are returned in a table. If you want all journeys arriving at stop_ids within the specified time range, set arrival to TRUE.

Journeys are defined by a "from" and "to" stop_id, a departure, arrival and travel time. Note that exact journeys (with each intermediate stop and route ids for example) are not returned.

For most cases, stop_times needs to be filtered, as it should only contain trips happening on a single day, see filter_stop_times(). The algorithm scans all trips until it exceeds max_transfers or all trips in stop_times have been visited.

See also

travel_times() for an easier access to travel time calculations via stop_names.

Examples

# \donttest{
nyc_path <- system.file("extdata", "nyc_subway.zip", package = "tidytransit")
nyc <- read_gtfs(nyc_path)

# you can use initial walk times to different stops in walking distance (arbitrary example values)
stop_ids_harlem_st <- c("301", "301N", "301S")
stop_ids_155_st <- c("A11", "A11N", "A11S", "D12", "D12N", "D12S")
walk_times <- data.frame(stop_id = c(stop_ids_harlem_st, stop_ids_155_st),
                         walk_time = c(rep(600, 3), rep(410, 6)), stringsAsFactors = FALSE)

# Use journeys departing after 7 AM with arrival time before 11 AM on 26th of June
stop_times <- filter_stop_times(nyc, "2018-06-26", 7*3600, 9*3600)

# calculate all journeys departing from Harlem St or 155 St between 7:00 and 7:30
rptr <- raptor(stop_times, nyc$transfers, walk_times$stop_id, time_range = 1800,
               keep = "all")

# add walk times to travel times
rptr <- merge(rptr, walk_times, by.x = "from_stop_id", by.y = "stop_id")
rptr$travel_time_incl_walk <- rptr$travel_time + rptr$walk_time

# get minimal travel times (with walk times) for all stop_ids
library(data.table)
#> 
#> Attaching package: ‘data.table’
#> The following objects are masked from ‘package:dplyr’:
#> 
#>     between, first, last
shortest_travel_times <- setDT(rptr)[order(travel_time_incl_walk)][, .SD[1], by = "to_stop_id"]
hist(shortest_travel_times$travel_time, breaks = seq(0,2*60)*60)

# }