Prioritise road network lanes for bus lane implementation

For each OSM way with GTFS service, aggregates its characteristics to assist in the bus lane implementation prioritisation

Usage

prioritise_lanes(
  gtfs,
  q,
  date = GTFShift::calendar_nextBusinessWednesday(),
  keep_osm_attributes = FALSE,
  osm_file = NULL
)

Arguments

gtfs: tidygtfs. GTFS feed.
q: osmdata::opq. Overpass query for transit network, to obtain OSM route ways, using GTFShift::osm_shapes_to_routes().
date: Date (Default GTFShift::calendar_nextBusinessWednesday()). Reference date to consider when analyzing the GTFS file.
keep_osm_attributes: Boolean (Default FALSE). Whether to keep all OSM way attributes in the output sf object.
osm_file: character (Optional). Location of OSM extract file with osm.pbf format. Refer to osmextract::oe_download() for more details. If not provided OSM Overpass API is called through osmdata::osmdata_sf().

Value

sf data.frame. Prioritised lanes with the following columns:

way_osm_id: The osm_id attribute from OSM way.
hour: The hour for which the frequency applies (24 hour format).
frequency: The number of services for the route that depart from the first stop for the corresponding 60 minutes period.
is_bus_lane: Whether the way has a bus lane.
n_lanes_parking: The number of parking lanes.
n_lanes_circulation: The number of circulation lanes.
n_directions: The number of travel directions.
n_lanes_circulation_direction: The number of circulation lanes per direction.
routes: The list of route_id that use the way.
shapes: The list of shape_id that use the way.
geometry: The route shape.
(if keep_osm_attributes = TRUE): All OSM way attributes.

Details

This method analyses the GTFS feed for a representative day, returning a data.frame with the road segments where transit routes run and for each, a set of parameters that can be used to prioritise bus lane implementations.

Its functionality is a bundle that encapsulates the logic of several methods from the package, including GTFShift::get_way_frequency_hourly() and GTFShift::osm_bus_lanes(), that can be used separately if needed.

Mind that this method uses GTFShift::get_way_frequency_hourly() to match routes with OSM ways, which requires that the OSM relation mapping is well defined for the transit routes. Routes that do not have an OSM match are ignored.

Examples

# Subset GTFS for one route only, for demo purposes
gtfs <- GTFShift::load_feed(system.file("extdata/samples",
  "gtfs_tcb_sample.zip", package = "GTFShift")
)
gtfs <- GTFShift::filter_by_route_name(gtfs, c("4"))

# Build query and prepare osm extract (possible to use API as alternative)
q <- osmdata::opq(bbox = sf::st_bbox(tidytransit::shapes_as_sf(gtfs$shapes))) |> 
  osmdata::add_osm_feature(key = "route", value = "bus") |> 
  osmdata::add_osm_feature(key = "operator", value = "Transportes Colectivos do Barreiro")
osm_file <- system.file("extdata/samples", "osmextract_tcb_network.pbf", package = "GTFShift")

lane_prioritisation <- GTFShift::prioritise_lanes(
  gtfs, q, 
  osm_file = osm_file, 
  date = gtfs$calendar$start_date[1]
)
#> Analysing GTFS for 2026-06-08...
#> > Filtering by reference date 2026-06-08...
#> Matched 1 shapes (100.00% of 1 in GTFS) of 1 routes (100.00% of 1 in GTFS) with OSM routes!

head(
  lane_prioritisation |> 
  dplyr::select(way_osm_id, hour, frequency, is_bus_lane, n_lanes_circulation, routes)
)
#> Simple feature collection with 6 features and 6 fields
#> Geometry type: LINESTRING
#> Dimension:     XY
#> Bounding box:  xmin: -9.070888 ymin: 38.64434 xmax: -9.060215 ymax: 38.65214
#> Geodetic CRS:  WGS 84
#> # A tibble: 6 × 7
#>   way_osm_id  hour frequency is_bus_lane n_lanes_circulation routes   
#>   <chr>      <int>     <int> <lgl>                     <dbl> <list>   
#> 1 1020152013     5         1 FALSE                         2 <chr [1]>
#> 2 1020165026     5         1 FALSE                         2 <chr [1]>
#> 3 1020521795     5         1 FALSE                         2 <chr [1]>
#> 4 1020521796     5         1 FALSE                         1 <chr [1]>
#> 5 1020521810     5         1 FALSE                         2 <chr [1]>
#> 6 1020521811     5         1 FALSE                         2 <chr [1]>
#> # ℹ 1 more variable: geometry <LINESTRING [°]>