U-Shift · gmatosferreira · Feb 4, 2026 · Jan 22, 2026 · Jan 28, 2026 · Jan 28, 2026
diff --git a/NAMESPACE b/NAMESPACE
@@ -19,7 +19,7 @@ export(osm_shapes_to_routes)
 export(osm_trips_to_routes)
 export(prioritize_lanes)
 export(query_mobilitydatabase)
-export(query_mobilitydatabase)
+export(query_mobilitydatabase)
+export(rt_collect)
-export(query_mobilitydatabase)
+export(query_mobilitydatabase)
+export(rt_collect)
-export(rt_collect)
+export(rt_collect_json)
 export(rt_collect_protobuf)
 export(rt_extend_prioritization)
 export(unify)

diff --git a/R/get_route_frequency_hourly.R b/R/get_route_frequency_hourly.R
@@ -92,13 +92,12 @@ get_route_frequency_hourly = function(
       "stop_sequence"
     )))
 
-  stop_times = stop_times |> # Only departures from origin (first stop)
-    filter(stop_sequence == 1)
-
   stop_times = stop_times |>
-    mutate(
-      hour = lubridate::hour(departure_time)
-    )
+    arrange(stop_sequence) |>
+    group_by(trip_id) |>
+    slice(1) |> # Only departures from origin (first stop)
+    ungroup() |>
+    mutate(hour = lubridate::hour(departure_time))
 
   freq_data = stop_times |>
     group_by(across(any_of(c("route_id", "route_short_name", "direction_id", "hour")))) |>

diff --git a/R/get_way_frequency_hourly.R b/R/get_way_frequency_hourly.R
@@ -18,6 +18,7 @@
 #'  \item \code{way_osm_id}, the \code{osm_id} attribute from OSM way.
 #'  \item \code{hour}, the hour for which the frequency applies (24 hour format).
 #'  \item \code{frequency}, the number of services for the route that depart from the first stop for the corresponding 60 minutes period.
+#'  \item \code{routes}, the list of route_ids that use the way, separated by semicolon.
 #'  \item \code{geometry}, the route shape.
 #'  \item (if \code{keep_osm_attributes = TRUE}) all OSM way attributes.
 #' }
@@ -75,13 +76,12 @@ get_way_frequency_hourly = function(
       "stop_sequence"
     )))
 
-  stop_times = stop_times |> # Only departures from origin (first stop)
-    filter(stop_sequence == 1)
-
   stop_times = stop_times |>
-    mutate(
-      hour = lubridate::hour(departure_time)
-    )
+    arrange(stop_sequence) |>
+    group_by(trip_id) |>
+    slice(1) |> # Only departures from origin (first stop)
+    ungroup() |>
+    mutate(hour = lubridate::hour(departure_time))
 
   freq_data = stop_times |>
     group_by(across(any_of(c("route_id", "route_short_name", "direction_id", "hour")))) |>
@@ -107,7 +107,10 @@ get_way_frequency_hourly = function(
   ways_freq = routes_freq |>
     inner_join(ways |> sf::st_drop_geometry() |> select(shape_id, way_osm_id), by="shape_id", relationship = "many-to-many") |>
     group_by(way_osm_id, hour) |>
-    summarize(frequency = sum(frequency)) |>
+    summarize(
+      frequency = sum(frequency),
+      routes = paste(unique(route_id), collapse = ";")
+    ) |>
     ungroup() |>
     inner_join(ways_unique_geometry, by="way_osm_id") |>
     st_as_sf()

diff --git a/R/prioritize_lanes.R b/R/prioritize_lanes.R
@@ -26,6 +26,7 @@
 #'  \item \code{n_lanes}, the total number of lanes.
 #'  \item \code{n_directions}, the number of travel directions.
 #'  \item \code{n_lanes_direction}, the number of lanes per direction.
+#'  \item \code{routes}, the list of route_ids that use the way, separated by semicolon.
 #'  \item \code{geometry}, the route shape.
 #'  \item (if \code{keep_osm_attributes = TRUE}) all OSM way attributes.
 #' }
@@ -84,19 +85,21 @@ prioritize_lanes <- function(
         2 # NA_integer_
       ),
       n_directions = case_when(
+        n_lanes == 1 ~ 1, # When only one lane, assume one direction
         oneway %in% c("yes", "1", "-1", "true") ~ 1,
         oneway %in% c("no", "0", "false") ~ 2,
         TRUE ~ 2
       ),
       n_lanes_direction = case_when(
+        n_lanes / n_directions < 1 ~ 1,
         !is.na(n_lanes) & !is.na(n_directions) ~ n_lanes / n_directions,
         TRUE ~ NA_real_
       )
     )
 
   if (!keep_osm_attributes) {
     lanes = lanes |>
-      select(way_osm_id, hour, frequency, is_bus_lane, n_lanes, n_directions, n_lanes_direction, geometry)
+      select(way_osm_id, hour, frequency, is_bus_lane, n_lanes, n_directions, n_lanes_direction, routes, geometry)
   }
 
   return(lanes)

diff --git a/R/query_osm_bus_lanes.R b/R/query_osm_bus_lanes.R
@@ -36,8 +36,8 @@ osm_bus_lanes <- function(bbox) {
     # Based on https://wiki.openstreetmap.org/wiki/Bus_lanes
     psv == "designated"
     | highway == "busway"
-    | if_any(all_of(cols_to_check_access), ~ grepl("designated", .x))
-    | if_any(all_of(cols_to_check_count), ~ is.numeric(.x) & .x >= 1)
+    | (length(cols_to_check_access) & if_any(all_of(cols_to_check_access), ~ grepl("designated", .x)))
+    | (length(cols_to_check_count) & if_any(all_of(cols_to_check_count), ~ is.numeric(.x) & .x >= 1))
   )
 
   return(osm_lanes)

diff --git a/R/query_osm_shapes_match_routes.R b/R/query_osm_shapes_match_routes.R
@@ -314,7 +314,7 @@ osm_shapes_match_routes <- function(gtfs, q, geometry = TRUE, gtfs_match = "rout
         route_dist = st_length(geometry) |> units::drop_units(),
         trip_id_copy = trip_id,
 
-        first_stop_id = gtfs$stop_times |> filter(trip_id == trip_id_copy & stop_sequence == 1) |> slice(1) |> pull(stop_id),
+        first_stop_id = gtfs$stop_times |> filter(trip_id == trip_id_copy) |> arrange(stop_sequence) |> slice(1) |> pull(stop_id),
         last_stop_id = gtfs$stop_times |> filter(trip_id == trip_id_copy) |> arrange(desc(stop_sequence)) |> slice(1) |> pull(stop_id),
         initial = stops_sf |> filter(stop_id == first_stop_id) |> slice(1) |> pull(geometry),
         final = stops_sf |> filter(stop_id == last_stop_id) |> slice(1) |> pull(geometry),

diff --git a/R/query_osm_shapes_to_routes.R b/R/query_osm_shapes_to_routes.R
@@ -137,12 +137,24 @@ osm_shapes_to_routes <- function(gtfs, q, ways = FALSE, ways_tags = c("lanes", "
     pb$terminate()
   }
 
-  # 4. Log missing shapes
-  message(sprintf("Matched %d shapes with OSM routes!", length(unique(result$shape_id))))
-  shapes_missing = shape_ids |> filter(!(shape_id %in% result$shape_id)) |> left_join(gtfs$trips, by="shape_id") |> left_join(gtfs$routes, by="route_id") |> distinct(shape_id, .keep_all = TRUE)
-  if (nrow(shapes_missing)>0) {
-    row_strings <- with(shapes_missing, sprintf("%s (%s)", shape_id, route_short_name))
-    warning(sprintf("Shapes missing (ignored in the result): %s", paste(row_strings, collapse = " ")))
+  # 4. Log missing shapes/routes
+  routes_shapes = gtfs$routes |> select(route_id, route_short_name, route_long_name) |>
+    right_join(gtfs$trips |> select(trip_id, route_id, shape_id), by="route_id") |>
+    distinct(route_id, shape_id, .keep_all = TRUE)
+
+  shapes_matched_n = result |> distinct(shape_id) |> nrow()
+  shapes_gtfs_n = gtfs$shapes |> distinct(shape_id) |> nrow()
+  routes_matched_n = routes_shapes |> filter(shape_id %in% result$shape_id) |> distinct(route_id) |> nrow()
+  routes_gtfs_n = gtfs$routes |> distinct(route_id) |> nrow()
+
+  message(sprintf("Matched %d shapes (%.2f%% of %d in GTFS) of %d routes (%.2f%% of %d in GTFS) with OSM routes!",
+      shapes_matched_n, shapes_matched_n/shapes_gtfs_n*100, shapes_gtfs_n,
+      routes_matched_n, routes_matched_n/routes_gtfs_n*100, routes_gtfs_n
+  ))
+  routes_shapes_missing = routes_shapes |> filter(!(shape_id %in% result$shape_id))
+  if (nrow(routes_shapes_missing)>0) {
+    row_strings <- with(routes_shapes_missing, sprintf("| %s | %s | %s | %s |", route_id, shape_id, route_short_name, route_long_name))
+    warning(sprintf("Shapes missing (ignored in the result):\n| route_id | shape_id | route_short_name | route_long_name |\n%s", paste(row_strings, collapse = "\n")))
   }
 
   return(result)

diff --git a/R/rt_collect.R → R/rt_collect_json.R b/R/rt_collect.R → R/rt_collect_json.R
@@ -1,4 +1,4 @@
-#' Collect GTFS-RT data
+#' Collect GTFS-RT data from a JSON feed at regular intervals
 #'
 #'
 #' @param gtfs_rt_url String. URL of the GTFS-RT feed in JSON format.
@@ -12,19 +12,19 @@
 #' @details
 #' Downloads GTFS-RT data from the specified URL at regular intervals and saves them to the destination file.
 #'
-#' This function will run indefinitely until manually stopped.
+#' This function will run indefinitely until manually stopped (CTRL + C).
 #'
 #'
 #' @examples
 #' \dontrun{
-#' GTFShift::rt_collect("https://api.example.com/gtfs-rt", "gtfs_rt_data.csv")
+#' GTFShift::rt_collect_json("https://api.example.com/gtfs-rt", "gtfs_rt_data.csv")
 #' }
 #'
 #' @import jsonlite
 #' @import progress
 #'
 #' @export
-rt_collect <- function(
+rt_collect_json <- function(
     gtfs_rt_url, destination_file,
     header_key="header", # Optional
     entity_key="entity",

diff --git a/R/rt_collect_protobuf.R b/R/rt_collect_protobuf.R
@@ -1,4 +1,4 @@
-#' Collect GTFS-RT data (with Protocol Buffers support)
+#' Collect GTFS-RT data from a Protocol Buffers feed at regular intervals
 #'
 #'
 #' @param gtfs_rt_url String. URL of the Protocol Buffers GTFS-RT feed.
@@ -10,7 +10,7 @@
 #' @details
 #' Downloads GTFS-RT data from the specified URL at regular intervals and saves them to the destination file.
 #'
-#' This function will run indefinitely until manually stopped. Each downloaded file is named with a timestamp to ensure uniqueness.
+#' This function will run indefinitely until manually stopped (CTRL + C).
 #'
 #'
 #' @examples
@@ -78,7 +78,7 @@ rt_collect_protobuf <- function(
     )
 
     suppressMessages({
-      rt_collect(
+      rt_collect_json(
         gtfs_rt_url = temp_json,
         destination_file = destination_file,
         fields_collect = fields_collect,

diff --git a/R/rt_extend_prioritization.R b/R/rt_extend_prioritization.R
@@ -9,7 +9,7 @@
 #' @details
 #' Extends the \code{lane_prioritization} data with speed metrics calculated from the GTFS-RT data points that fall within a buffer around each lane segment.
 #'
-#' Refer to \code{GTFShift::rt_collect()} for details on GTFS-RT data collection.
+#' Refer to \code{GTFShift::rt_collect_json()} or \code{GTFShift::rt_collect_protobuf()} for details on GTFS-RT data collection.
 #'
 #'
 #' @returns The \code{lane_prioritization} \code{sf} \code{data.frame}, extended with the following columns:
@@ -24,7 +24,7 @@
 #' @examples
 #' \dontrun{
 #' rt_collect_file <- "gtfs_rt_data.csv"
-#' GTFShift::rt_collect("https://api.example.com/gtfs-rt", rt_collect_file)
+#' GTFShift::rt_collect_json("https://api.example.com/gtfs-rt", rt_collect_file)
 #' lane_prioritization <- GTFShift::prioritize_lanes(gtfs, osm_query)
 #'
 #' rt_collection <- read.csv(rt_collect_file) |> sf::st_as_sf(coords = c("longitude", "latitude"), crs = 4326)
@@ -45,7 +45,7 @@ rt_extend_prioritization <- function(
   lane_buffer = 15 # in meters
 ) {
   # 1. Validate inputs
-  required_cols = c("way_osm_id", "geometry")
+  required_cols = c("way_osm_id")
   missing_cols = setdiff(required_cols, colnames(lane_prioritization))
   if (length(missing_cols) > 0) {
     stop(paste("lane_prioritization is missing required columns:", paste(missing_cols, collapse = ", ")))

diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-# GTFShift
+# GTFShift <img align="right" src="man/figures/logo.png" alt="logo" width="180">
 
 <!-- badges: start -->
 [![](https://github.com/U-Shift/GTFShift/actions/workflows/pkgdown.yaml/badge.svg)](https://github.com/U-Shift/GTFShift/actions/workflows/pkgdown.yaml)
@@ -8,48 +8,22 @@
 overview of where bus lanes should be prioritized for a given territory,
 using General Transit Feed Specification (GTFS) and OpenStreetMap (OSM) data.
 
-It provides a simple bundle for an aggregated analysis, that with one execution 
-compiles in a few seconds the following indicators:
+It provides a comprehensive bundle of methods that cover several dimensions of this 
+problem, namely:
 
 -   Frequency of buses (and trams) per hour and direction, at a peak hour;
--   Number of lanes in the same direction.
+-   Number of lanes in the same direction;
+-   Existing traffic conditions;
+-   Existing bus lanes in the area (from a network continuity perspective).
 
 Together, these can be used to identify road segments where bus lanes should be implemented, 
 enabling for a transparent and data-driven decision-making process, suitable to different contexts
 and criteria. 
 
-```r
-library(GTFShift)
-library(osmdata)
-
-data = read.csv(system.file("extdata", "gtfs_sources_pt.csv", package = "GTFShift"))
-gtfs_id = "lisboa"
-gtfs = GTFShift::load_feed(data$URL[data$ID == gtfs_id], create_transfers=FALSE)
-osm_q = opq(bbox=sf::st_bbox(tidytransit::shapes_as_sf(gtfs$shapes)))  |>
-  add_osm_feature(key = "route", value = c("bus", "tram")) |>
-  add_osm_feature(key = "network", value = "Carris", key_exact = TRUE)
-
-lanes = prioritize_lanes(gtfs, osm_q)
-
-mapview::mapview(
-  lanes |> filter((frequency<=4 | (is.na(n_lanes) | n_lanes_direction<=1)) & is_bus_lane),
-  layer.name="Bus lane with - 5 bus/h OR - 1 lane/dir",
-  color="#DAD887"
-) + mapview::mapview(
-  lanes |> filter(frequency>=5 & !is.na(n_lanes) & n_lanes_direction>1 & is_bus_lane),
-  layer.name="Bus lane with 5 or + bus/h + 1 lane/dir",
-  color="#3BC1A8"
-) + mapview::mapview(
-  lanes |> filter(frequency>=5 & !is.na(n_lanes) & n_lanes_direction>1 & !is_bus_lane),
-  layer.name="NO bus lane with 5 or + bus/h + 1 lane/dir",
-  color="#F63049"
-)
-```
-
 ![](man/figures/prioritization.png)
 
 > Example of bus lane prioritization analysis for Lisbon city, considering road segments with
-a minimum frequency of 5 buses/hour and more than 1 lane per direction. 
+a minimum frequency of 10 buses/hour, average commercial speed below 9.7 km/h and more than 1 lane per direction. 
 
 ## Installation
 
@@ -67,72 +41,18 @@ remotes::install_github("U-Shift/GTFShift")
 library(GTFShift)
 ```
 
-## Key functions
-
-**GTFShift** provides methods for the entire workflow of bus network
-density analysis. For detailed examples on their functionality, refer to
-the articles at <https://u-shift.github.io/GTFShift/>.
-
-### Getting transit data
-
-Starting with a valid GTFS feed is the key for a successful analysis.
-**GTFShift** includes a method to load feeds that simultaneously scans
-for any integrity errors and fixes them automatically.
-
-If the feed location is unknown, it also provides a database listing
-GTFS for Portugal and a method to query worldwide open catalogues by
-city or country names or even a bounding box.
-
-### Filter
-
-GTFS feeds do not have a defined scope regarding its coverage of the
-transportation system. Some can be bounded to one agency, whereas others
-can aggregate several modes in the same city, or even national wise.
-
-From the simpler to the most complex feeds, some analysis require to
-narrow the perspective. **GTFShift** provides some to help in this
-process.
-
-### Aggregate
-
-Public transit analysis takes advantage of the standardized GTFS format.
-However, its provision by operator makes it difficult for network
-aggregated analysis, considering connectivity and multimodality.
-
-**GTFShift** includes a method to easily generate an aggregated GTFS
-file given several instances.
-
-![](man/figures/unify.png)
-
-> Aggregated GTFS for Fertagus and Transportes Coletivos do Barreiro
-> operators
-
-### Analyse
-
-Analyzing public transit feeds is important to understand its
-territorial coverage and dynamics, both on its spatial and temporal
-dimensions.
-
-**GTFShift** provides several methods that encapsulate pre-defined
-methodologies for them, for instance, analysing hourly frequency per
-stop, route or road segment.
-
-![](man/figures/analyse_aggregated_frequencies.png)
-
-> Aggregated route frequency for Carris Lisboa operator, at 8:00
+## Get started
 
-### OSM Data
+For more details on the package and how to get started, please visit the [Get started](https://u-shift.github.io/GTFShift/articles/GTFShift.html) page.
 
-OpenStreetMaps (OSM) is an important data source for transit analysis,
-due to its rich, open, and detailed geographic data.
+## Dashboard 
 
-**GTFShift** includes some methods that allow to access its information
-directly, namely to export bus lanes, get centerlines for the road
-network and export the OSM transit routes.
+**GTFShift** provides an interactive dashboard that allows users to explore and visualize results for real case studies, 
+aiming to illustrate its potential and capabilities to a non-technical audience, while disseminating the outputs of these real world scenarios.
 
-![](man/figures/osm_buslanes.png)
+Visit it at [ushift.pt/apps/gtfshift](https://ushift.pt/apps/gtfshift).
 
-> OSM exported bus lanes for Lisbon
+[![](man/figures/web.png)](https://ushift.pt/apps/gtfshift)
 
 ## Related packages
 
@@ -144,7 +64,7 @@ network and export the OSM transit routes.
 ## Acknowledgement
 
 **GTFShift** is developed and maintained by
-[U-shift](https://ushift.tecnico.ulisboa.pt) urban mobility research
+[U-Shift](https://ushift.tecnico.ulisboa.pt) urban mobility research
 group, part of [CERIS](https://ceris.pt/) research unit, at [Instituto
 Superior Técnico](https://tecnico.ulisboa.pt/pt/), Lisbon, Portugal.
 

diff --git a/_pkgdown.yml b/_pkgdown.yml
@@ -1,6 +1,20 @@
 url: https://u-shift.github.io/GTFShift/
 template:
   bootstrap: 5
+  light-switch: true
+  bslib:
+    primary: "#15AF97FF"
+
+navbar:
+  structure:
+   left:  [intro, reference, articles, dashboard]
+
+  components:
+    dashboard:
+      text: "Dashboard"
+      href: "https://ushift.pt/apps/gtfshift"
+      target: "_blank"
+
 
 reference:
   - title: Get GTFS feeds