diff --git a/Docs/core_concepts.md b/Docs/core_concepts.md
index ce87df825..047588653 100644
--- a/Docs/core_concepts.md
+++ b/Docs/core_concepts.md
@@ -81,7 +81,7 @@ Keep reading to learn more. Visit the forum to post any doubts or suggestions th
diff --git a/Docs/core_map.md b/Docs/core_map.md
index 67b1d09a3..a7cf3edfc 100644
--- a/Docs/core_map.md
+++ b/Docs/core_map.md
@@ -2,72 +2,95 @@
After discussing about the world and its actors, it is time to put everything into place and understand the map and how do the actors navigate it.
-* [__The map__](#the-map)
- * [Changing the map](#changing-the-map)
- * [Landmarks](#landmarks)
- * [Lanes](#lanes)
- * [Junctions](#junctions)
- * [Waypoints](#waypoints)
-* [__Navigation in CARLA__](#navigation-in-carla)
- * [Navigating through waypoints](#navigating-through-waypoints)
- * [Generating a map navigation](#generating-a-map-navigation)
-* [__CARLA maps__](#carla-maps)
+- [__The map__](#the-map)
+ - [Changing the map](#changing-the-map)
+ - [Landmarks](#landmarks)
+ - [Lanes](#lanes)
+ - [Junctions](#junctions)
+ - [Waypoints](#waypoints)
+ - [Environment Objects](#environment-objects)
+- [__Navigation in CARLA__](#navigation-in-carla)
+ - [Navigating through waypoints](#navigating-through-waypoints)
+ - [Generating a map navigation](#generating-a-map-navigation)
+- [__CARLA maps__](#carla-maps)
+ - [Non-layered maps](#non-layered-maps)
+ - [Layered maps](#layered-maps)
---
## The map
-A map includes both the 3D model of a town and its road definition. Every map is based on an OpenDRIVE file describing the road layout fully annotated. The way the [OpenDRIVE standard 1.4](http://www.opendrive.org/docs/OpenDRIVEFormatSpecRev1.4H.pdf) defines roads, lanes, junctions, etc. is extremely important. It determines the possibilities of the API and the reasoning behind decisions made.
+A map includes both the 3D model of a town and its road definition. A map's road definition is based on an OpenDRIVE file, a standarized, annotated road definition format. The way the [OpenDRIVE standard 1.4](http://www.opendrive.org/docs/OpenDRIVEFormatSpecRev1.4H.pdf) defines roads, lanes, junctions, etc. determines the functionality of the Python API and the reasoning behind decisions made.
-The Python API makes for a high level querying system to navigate these roads. It is constantly evolving to provide a wider set of tools.
+The Python API acts as a high level querying system to navigate these roads. It is constantly evolving to provide a wider set of tools.
### Changing the map
-__To change the map, the world has to change too__. Everything will be rebooted and created from scratch, besides the Unreal Editor itself. There are two ways to do so.
+__To change the map, the world has to change too__. The simulation will be recreated from scratch. You can either restart with the same map in a new world or you can change both the map and the world:
-* `reload_world()` creates a new instance of the world with the same map.
-* `load_world()` changes the current map and creates a new world.
+- `reload_world()` creates a new instance of the world with the same map.
+- `load_world()` changes the current map and creates a new world.
```py
world = client.load_world('Town01')
```
-The client can get a list of available maps. Each map has a `name` attribute that matches the name of the currently loaded city, e.g. _Town01_.
+
+Each map has a `name` attribute that matches the name of the currently loaded city, e.g. _Town01_. To get a list of the available maps:
+
```py
print(client.get_available_maps())
```
### Landmarks
-The traffic signs defined in the OpenDRIVE file are translated into CARLA as landmark objects that can be queried from the API. In order to facilitate their manipulation, there have been several additions to it.
+Traffic signs defined in the OpenDRIVE file are translated to CARLA as landmark objects that can be queried from the API. The following methods and classes can be used to manipulate and work with landmark objects:
-* __[carla.Landmark](https://carla.readthedocs.io/en/latest/python_api/#carla.Landmark)__ objects represent the OpenDRIVE signals. The attributes and methods describe the landmark, and where it is effective.
- * [__carla.LandmarkOrientation__](https://carla.readthedocs.io/en/latest/python_api/#carla.LandmarkOrientation) states the orientation of the landmark with regards of the road's geometry definition.
- * [__carla.LandmarkType__](https://carla.readthedocs.io/en/latest/python_api/#carla.LandmarkType) contains some common landmark types, to ease translation to OpenDRIVE types.
-* A __[carla.Waypoint](https://carla.readthedocs.io/en/latest/python_api/#carla.Waypoint)__ can get landmarks located a certain distance ahead of it. The type of landmark can be specified.
-* The __[carla.Map](https://carla.readthedocs.io/en/latest/python_api/#carla.Map)__ retrieves sets of landmarks. It can return all the landmarks in the map, or those having an ID, type or group in common.
-* The __[carla.World](https://carla.readthedocs.io/en/latest/python_api/#carla.World)__ acts as intermediary between landmarks, and the *carla.TrafficSign* and *carla.TrafficLight* that embody them in the simulation.
+- __[`carla.Landmark`](https://carla.readthedocs.io/en/latest/python_api/#carla.Landmark)__ objects represent OpenDRIVE signals. The attributes and methods of this class describe the landmark and its area of influence.
+ - [`carla.LandmarkOrientation`](https://carla.readthedocs.io/en/latest/python_api/#carla.LandmarkOrientation) states the orientation of the landmark with regard to the road's geometry definition.
+ - [`carla.LandmarkType`](https://carla.readthedocs.io/en/latest/python_api/#carla.LandmarkType) contains common landmark types to facilitate translation to OpenDRIVE types.
+- __[`carla.Waypoint`](https://carla.readthedocs.io/en/latest/python_api/#carla.Waypoint)__ can get landmarks located a certain distance ahead of it. The landmark type to get can be specified.
+- __[`carla.Map`](https://carla.readthedocs.io/en/latest/python_api/#carla.Map)__ retrieves sets of landmarks. It can return all landmarks in the map, or those which have a common ID, type or group.
+- __[`carla.World`](https://carla.readthedocs.io/en/latest/python_api/#carla.World)__ acts as intermediary between landmarks and the `carla.TrafficSign` and `carla.TrafficLight` that represent them in the simulation.
```py
my_waypoint.get_landmarks(200.0,True)
```
-### Lanes
+### Waypoints
-The lane types defined by [OpenDRIVE standard 1.4](http://www.opendrive.org/docs/OpenDRIVEFormatSpecRev1.4H.pdf) are translated to the API in [__carla.LaneType__](python_api.md#carla.LaneType) as a series of enum values.
+A [`carla.Waypoint`](python_api.md#carla.Waypoint) is a 3D-directed point in the CARLA world corresponding to an OpenDRIVE lane. Everything related to waypoints happens on the client-side; communication with the server is only needed once to get the [map object](python_api.md#carlamap) containing the waypoint information.
-The lane markings surrounding a lane can be accessed through [__carla.LaneMarking__](python_api.md#carla.LaneMarking). These are defined with a series of variables.
+Each waypoint contains a [`carla.Transform`](python_api.md#carla.Transform) which states its location on the map and the orientation of the lane containing it. The variables `road_id`,`section_id`,`lane_id` and `s` correspond to the OpenDRIVE road. The `id` of the waypoint is constructed from a hash combination of these four values.
-* [__carla.LaneMarkingType__](python_api.md#carla.LaneMarkingType) are enum values according to OpenDRIVE standards.
-* [__carla.LaneMarkingColor__](python_api.md#carla.LaneMarkingColor) are enum values to determine the color of the marking.
-* __width__ to state thickness of the marking.
-* [__carla.LaneChange__](python_api.md#carla.LaneChange) to state permissions to perform lane changes.
+!!! Note
+ Waypoints closer than __2cm within the same road__ share the same `id`.
-Waypoints use these to aknowledge traffic permissions.
+A waypoint holds information about the __lane__ containing it. This information includes the lane's left and right __lane markings__, a boolean to determine if it's inside a junction, the lane type, width, and lane changing permissions.
```py
-# Get the lane type where the waypoint is.
+# Access lane information from a waypoint
+inside_junction = waypoint.is_junction()
+width = waypoint.lane_width
+right_lm_color = waypoint.right_lane_marking.color
+```
+
+### Lanes
+
+The lane types defined by [OpenDRIVE standard 1.4](http://www.opendrive.org/docs/OpenDRIVEFormatSpecRev1.4H.pdf) are translated to the API in [`carla.LaneType`](python_api.md#carla.LaneType) as a series of enum values.
+
+The lane markings surrounding a lane are accessed through [`carla.LaneMarking`](python_api.md#carla.LaneMarking). Lane markings are defined by a series of variables:
+
+- __color:__ [`carla.LaneMarkingColor`](python_api.md#carla.LaneMarkingColor) are enum values that define the marking's color.
+- __lane_change:__ [`carla.LaneChange`](python_api.md#carla.LaneChange) states if the lane permits turning left, right, both or none.
+- __type:__ [`carla.LaneMarkingType`](python_api.md#carla.LaneMarkingType) are enum values that define the type of marking according to the OpenDRIVE standard.
+- __width:__ defines the marking's thickness.
+
+The below example shows to get information about the lane type, lane markings, and lane change permissions at a specific waypoint:
+
+```py
+# Get the lane type of the waypoint
lane_type = waypoint.lane_type
-# Get the type of lane marking on the left.
+# Get the type of lane marking on the left.
left_lanemarking_type = waypoint.left_lane_marking.type()
# Get available lane changes for this waypoint.
@@ -76,98 +99,110 @@ lane_change = waypoint.lane_change
### Junctions
-A [carla.Junction](python_api.md#carla.Junction) represents an OpenDRIVE junction. This class provides for a bounding box to state whereas lanes or vehicles are inside of it.
+A [`carla.Junction`](python_api.md#carla.Junction) represents an OpenDRIVE junction. This class encompasses a junction with a bounding box to identify lanes or vehicles within it.
-The most remarkable method of this class returns a pair of waypoints per lane inside the junction. Each pair is located at the starting and ending point of the junction boundaries.
+The `carla.Junction` class contains the `get_waypoints` method which returns a pair of waypoints for every lane within the junction. Each pair is located at the start and end points of the junction boundaries.
```py
waypoints_junc = my_junction.get_waypoints()
```
-### Waypoints
+### Environment Objects
-A [__carla.Waypoint__](python_api.md#carla.Waypoint) is a 3D-directed point. These are prepared to mediate between the world and the openDRIVE definition of the road. Everything related with waypoints happens on the client-side, so there no communication with the server is needed.
+Every object on a CARLA map has a set of associated variables which can be found [here][env_obj]. Included in these variables is a [unique ID][env_obj_id] that can be used to [toggle][toggle_env_obj] that object's visibility on the map. You can use the Python API to [fetch][fetch_env_obj] the IDs of each environment object based on their [semantic tag][semantic_tag]:
-Each waypoint contains a [carla.Transform](python_api.md#carla.Transform). This states its location on the map and the orientation of the lane containing it. The variables `road_id`,`section_id`,`lane_id` and `s` translate this transform to the OpenDRIVE road. These combined, create the `id` of the waypoint.
+ # Get the buildings in the world
+ world = client.get_world()
+ env_objs = world.get_environment_objects(carla.CityObjectLabel.Buildings)
-!!! Note
- Due to granularity, waypoints closer than __2cm within the same road__ share the same `id`.
+ # Access individual building IDs and save in a set
+ building_01 = env_objs[0]
+ building_02 = env_objs[1]
+ objects_to_toggle = {building_01.id, building_02.id}
-A waypoint also contains some information regarding the __lane__ containing it. Specifically its left and right __lane markings__, and a boolean to determine if it is inside a junction.
+ # Toggle buildings off
+ world.enable_environment_objects(objects_to_toggle, False)
+ # Toggle buildings on
+ world.enable_environment_objects(objects_to_toggle, True)
+
+See an example of distinct objects being toggled:
+
+
+
+[env_obj]: https://carla.readthedocs.io/en/latest/python_api/#carla.EnvironmentObject
+[env_obj_id]: https://carla.readthedocs.io/en/latest/python_api/#carla.EnvironmentObject.id
+[toggle_env_obj]: https://carla.readthedocs.io/en/latest/python_api/#carla.World.enable_environment_objects
+[fetch_env_obj]: https://carla.readthedocs.io/en/latest/python_api/#carla.World.get_environment_objects
+[semantic_tag]: https://carla.readthedocs.io/en/latest/python_api/#carla.CityObjectLabel
-```py
-# Examples of a waypoint accessing to lane information
-inside_junction = waypoint.is_junction()
-width = waypoint.lane_width
-right_lm_color = waypoint.right_lane_marking.color
-```
---
## Navigation in CARLA
-Navigation in CARLA is managed via the waypoint API. This consists of a summary of methods in [carla.Waypoint](python_api.md#carla.Waypoint) and [carla.Map](python_api.md#carla.Map).
-
-All the queries happen on the client-side. The client only communicates with the server when retrieving the map object that will be used for the queries. There is no need to retrieve the map (`world.get_map()`) more than once.
+Navigation in CARLA is managed via the Waypoint API, a combination of methods from [`carla.Waypoint`](python_api.md#carla.Waypoint) and [`carla.Map`](python_api.md#carla.Map).
+The client must initially communicate with the server to retrieve the map object containing the waypoint information. This is only required once, all subsequent queries are performed on the client side.
### Navigating through waypoints
-Waypoints have a set of methods to connect with others and create a road flow. All of these methods follow traffic rules to determine only places where the vehicle can go.
+The Waypoint API exposes methods that allow waypoints to connect to each other and construct a path along a road for vehicles to navigate:
+
+- `next(d)` creates a list of waypoints within an approximate distance, `d`, __in the direction of the lane__. The list contains one waypoint for each possible deviation.
+- `previous(d)` creates a list of waypoints waypoint within an approximate distance, `d`, __in the opposite direction of the lane__. The list contains one waypoint for each possible deviation.
+- `next_until_lane_end(d)` and `previous_until_lane_start(d)` return a list of waypoints a distance `d` apart. The lists go from the current waypoint to the end and beginning of its lane, respectively.
+- `get_right_lane()` and `get_left_lane()` return the equivalent waypoint in an adjacent lane, if one exists. A lane change maneuver can be made by finding the next waypoint to the one on its right/left lane, and moving to it.
-* `next(d)` creates a list of waypoints at an approximate distance `d` __in the direction of the lane__. The list contains one waypoint for each deviation possible.
-* `previous(d)` creates a list of waypoints waypoint at an approximate distance `d` __on the opposite direction of the lane__. The list contains one waypoint for each deviation possible.
-* `next_until_lane_end(d)` and `previous_until_lane_start(d)` returns a list of waypoints a distance `d` apart. The list goes from the current waypoint to the end and start of its lane, respectively.
-* `get_right_lane()` and `get_left_lane()` return the equivalent waypoint in an adjacent lane, if any. A lane change maneuver can be made by finding the next waypoint to the one on its right/left lane, and moving to it.
```py
-# Disable physics, in this example the vehicle is teleported.
-vehicle.set_simulate_physics(False)
-while True:
- # Find next waypoint 2 meters ahead.
- waypoint = random.choice(waypoint.next(2.0))
- # Teleport the vehicle.
- vehicle.set_transform(waypoint.transform)
-```
+# Find next waypoint 2 meters ahead.
+waypoint = waypoint.next(2.0)
+```
-### Generating a map navigation
+### Generating map navigation
-The instance of the map is provided by the world. It will be useful to create routes and make vehicles roam around the city and reach goal destinations.
+The client needs to make a request to the server to get the `.xodr` map file and parse it to a [`carla.Map`](python_api.md#carla.Map) object. This only needs to be done once.
-The following method asks the server for the XODR map file, and parses it to a [carla.Map](python_api.md#carla.Map) object. It only needs to be calle once. Maps can be quite heavy, and successive calls are unnecessary and expensive.
+To get the map object:
```py
map = world.get_map()
```
-* __Get recommended spawn points for vehicles__ pointed by developers. There is no ensurance that these spots will be free.
+The map object contains __recommended spawn points__ for the creation of vehicles. You can get a list of these spawn points, each one containing a [`carla.Transform`](python_api.md#carlatransform), using the method below. Bear in mind that the spawn points may be occupied already, resulting in failed creation of vehicles due to collisions.
+
```py
spawn_points = world.get_map().get_spawn_points()
```
-* __Get the closest waypoint__ to a specific location or to a certain `road_id`, `lane_id` and `s` in OpenDRIVE.
+You can get started with waypoints by __[getting](python_api.md#carla.Map.get_waypoint) the closest waypoint__ to a specific location or to a particular `road_id`, `lane_id` and `s` value in the map's OpenDRIVE definition:
+
```py
-# Nearest waypoint on the center of a Driving or Sidewalk lane.
+# Nearest waypoint in the center of a Driving or Sidewalk lane.
waypoint01 = map.get_waypoint(vehicle.get_location(),project_to_road=True, lane_type=(carla.LaneType.Driving | carla.LaneType.Sidewalk))
#Nearest waypoint but specifying OpenDRIVE parameters.
waypoint02 = map.get_waypoint_xodr(road_id,lane_id,s)
```
-* __Generate a collection of waypoints__ to visualize the city lanes. Creates waypoints all over the map, for every road and lane. All of them will be an approximate distance apart.
+The below example shows how to __generate a collection of waypoints__ to visualize the city lanes. This will create waypoints all over the map, for every road and lane. All of them will approximately 2 meters apart:
+
```py
waypoint_list = map.generate_waypoints(2.0)
```
-* __Generate road topology__. Returns a list of pairs (tuples) of waypoints. For each pair, the first element connects with the second one and both define the starting and ending point of each lane in the map.
+To __generate a minimal graph of road topology__, use the example below. This will return a list of pairs (tuples) of waypoints. The first element in each pair connects with the second element and both define the start and end points of each lane in the map. More information on this method is found in the [PythonAPI](python_api.md#carla.Map.get_topology).
+
```py
waypoint_tuple_list = map.get_topology()
```
-* __Convert simulation point to geographical coordinates.__ Transforms a certain location to a [carla.GeoLocation](python_api.md#carla.GeoLocation) with latitude and longitude values.
+The example below __converts a `carla.Transform` to geographical latitude and longitude coordinates,__ in the form of a [`carla.GeoLocation`](python_api.md#carla.GeoLocation):
+
```py
my_geolocation = map.transform_to_geolocation(vehicle.transform)
```
-* __Save road information.__ Converts the road information to OpenDRIVE format, and saves it to disk.
+Use the following example to __save road information__ in OpenDRIVE format to disk:
+
```py
info_map = map.to_opendrive()
```
@@ -175,51 +210,60 @@ info_map = map.to_opendrive()
---
## CARLA maps
-So far there are seven different maps available. Each one has unique features and is useful for different purposes. Hereunder is a brief sum up on them.
+There are eight towns in the CARLA ecosystem and each of those towns have two kinds of map, non-layered and layered. [Layers][layer_api] refer to the grouped objects within a map and consist of the following:
+
+- NONE
+- Buildings
+- Decals
+- Foliage
+- Ground
+- ParkedVehicles
+- Particles
+- Props
+- StreetLights
+- Walls
+- All
+
+[layer_api]: https://carla.readthedocs.io/en/latest/python_api/#carlamaplayer
+
+### Non-layered maps
+
+Non-layered maps are shown in the table below (click the town name to see an overhead image of the layout). All of the layers are present at all times and cannot be toggled on or off in these maps. Up until CARLA 0.9.11, these were the only kinds of map available.
!!! Note
- Users can [customize a map](tuto_A_map_customization.md) or even [create a new map](tuto_A_add_map.md) to be used in CARLA.
+ Users can [customize a map](tuto_A_map_customization.md) or even [create a new map](tuto_M_custom_map_overview.md) to be used in CARLA.
-| Town | Summary |
-| -------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- |
-| **Town01** | A basic town layout with all "T junctions". |
-| **Town02** | Similar to **Town01**, but smaller. |
-| **Town03** | The most complex town, with a 5-lane junction, a roundabout, unevenness, a tunnel, and much more. Essentially a medley. |
-| **Town04** | An infinite loop with a highway and a small town. |
-| **Town05** | Squared-grid town with cross junctions and a bridge. It has multiple lanes per direction. Useful to perform lane changes. |
-| **Town06** | Long highways with many highway entrances and exits. It also has a [**Michigan left**](
). |
-| **Town07** | A rural environment with narrow roads, barely non traffic lights and barns. |
-| **Town10** | A city environment with with different environments such as an avenue or a promenade, and more realistic textures. |
+| Town | Summary |
+| -----------| ------ |
+| **[Town01](img/Town01.jpg)** | A basic town layout consisting of "T junctions".|
+| **[Town02](img/Town02.jpg)** | Similar to **Town01**, but smaller.|
+| **[Town03](img/Town03.jpg)** | The most complex town, with a 5-lane junction, a roundabout, unevenness, a tunnel, and more.|
+| **[Town04](img/Town04.jpg)** | An infinite loop with a highway and a small town.|
+| **[Town05](img/Town05.jpg)** | Squared-grid town with cross junctions and a bridge. It has multiple lanes per direction. Useful to perform lane changes. |
+| **[Town06](img/Town06.jpg)** | Long highways with many highway entrances and exits. It also has a [**Michigan left**](). |
+| **[Town07](img/Town07.jpg)** | A rural environment with narrow roads, barns and hardly any traffic lights. |
+| **[Town10](img/Town10.jpg)** | A city environment with different environments such as an avenue or promenade, and more realistic textures.|
-
+### Layered maps
+The layout of layered maps is the same as non-layered maps but it is possible to toggle off and on the layers of the map. There is a minimum layout that cannot be toggled off and consists of roads, sidewalks, traffic lights and traffic signs. Layered maps can be identified by the suffix `_Opt`, for example, `Town01_Opt`. With these maps it is possible to [load][load_layer] and [unload][unload_layer] layers via the Python API:
-
-*Above: Town01*
+ # Load layered map for Town 01 with minimum layout plus buildings and parked vehicles
+ world = client.load_world('Town01_Opt', carla.MapLayer.Buildings | carla.MapLayer.ParkedVehicles)
-
-*Above: Town02*
+ # Toggle all buildings off
+ world.unload_map_layer(carla.MapLayer.Buildings)
-
-*Above: Town03*
+ # Toggle all buildings on
+ world.load_map_layer(carla.MapLayer.Buildings)
-
-*Above: Town04*
+[load_layer]: https://carla.readthedocs.io/en/latest/python_api/#carla.World.load_map_layer
+[unload_layer]: https://carla.readthedocs.io/en/latest/python_api/#carla.World.unload_map_layer
-
-*Above: Town05*
+See an example of all layers being loaded and unloaded in sequence:
-
-*Above: Town06*
+
-
-*Above: Town07*
-
-
-*Above: Town10*
-
-
-
---
That is a wrap as regarding maps and navigation in CARLA. The next step takes a closer look into sensors types, and the data they retrieve.
@@ -228,7 +272,7 @@ Keep reading to learn more or visit the forum to post any doubts or suggestions
diff --git a/Docs/core_sensors.md b/Docs/core_sensors.md
index b739f1f40..ae1e79b2d 100644
--- a/Docs/core_sensors.md
+++ b/Docs/core_sensors.md
@@ -102,16 +102,18 @@ Sensor data differs a lot between sensor types. Take a look at the [sensors refe
### Cameras
-Take a shot of the world from their point of view. The helper class [carla.ColorConverter](python_api.md#carla.ColorConverter) will modify said image to represent different information.
+Take a shot of the world from their point of view. For cameras that return [carla.Image](<../python_api#carlaimage>), you can use the helper class [carla.ColorConverter](python_api.md#carla.ColorConverter) to modify the image to represent different information.
* __Retrieve data__ every simulation step.
-| Sensor | Output | Overview |
-| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| Depth | [carla.Image](<../python_api#carlaimage>) | Renders the depth of the elements in the field of view in a gray-scale map. |
-| RGB | [carla.Image](<../python_api#carlaimage>) | Provides clear vision of the surroundings. Looks like a normal photo of the scene. |
-| Semantic segmentation | [carla.Image](<../python_api#carlaimage>) | Renders elements in the field of view with a specific color according to their tags. |
+|Sensor |Output | Overview |
+| ----------------- | ---------- | ------------------ |
+| Depth | [carla.Image](<../python_api#carlaimage>) |Renders the depth of the elements in the field of view in a gray-scale map. |
+| RGB | [carla.Image](<../python_api#carlaimage>) | Provides clear vision of the surroundings. Looks like a normal photo of the scene. |
+| Optical Flow | [carla.Image](<../python_api#carlaimage>) | Renders the motion of every pixel from the camera. |
+| Semantic segmentation | [carla.Image](<../python_api#carlaimage>) | Renders elements in the field of view with a specific color according to their tags. |
+| DVS | [carla.DVSEventArray](<../python_api#carladvseventarray>) | Measures changes of brightness intensity asynchronously as an event stream. |
@@ -184,7 +186,7 @@ Python API reference
diff --git a/Docs/core_world.md b/Docs/core_world.md
index 79d54045c..586638e11 100644
--- a/Docs/core_world.md
+++ b/Docs/core_world.md
@@ -2,7 +2,7 @@
The client and the world are two of the fundamentals of CARLA, a necessary abstraction to operate the simulation and its actors.
-This tutorial goes from defining the basics and creation of these elements, to describing their possibilities. If any doubt or issue arises during the reading, the [CARLA forum](https://forum.carla.org/) is there to solve them.
+This tutorial goes from defining the basics and creation of these elements, to describing their possibilities. If any doubt or issue arises during the reading, the [CARLA forum](https://github.com/carla-simulator/carla/discussions/) is there to solve them.
* [__The client__](#the-client)
* [Client creation](#client-creation)
@@ -264,7 +264,7 @@ Keep reading to learn more. Visit the forum to post any doubts or suggestions th
diff --git a/Docs/download.md b/Docs/download.md
index e6f33e586..b011270e3 100644
--- a/Docs/download.md
+++ b/Docs/download.md
@@ -1,51 +1,52 @@
# Download
+### Latest Release
+
+- [CARLA 0.9.12](https://github.com/carla-simulator/carla/releases/tag/0.9.12/) - [Documentation](https://carla.readthedocs.io/en/0.9.12/)
+
### Nightly build
-> This is an automated build with the latest changes pushed to our "master"
-> branch. It contains the very last fixes and features that will be part of the
+> This is an automated build with the latest changes pushed to our `dev`
+> branch. It contains the very latest fixes and features that will be part of the
> next release, but also some experimental changes. Use at your own risk!
- [CARLA Nightly Build (Linux)](https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/Dev/CARLA_Latest.tar.gz)
- [CARLA Nightly Build (Windows)](https://carla-releases.s3.eu-west-3.amazonaws.com/Windows/Dev/CARLA_Latest.zip)
-### Development [[Documentation](https://carla.readthedocs.io/en/latest/)]
+### Versions 0.9.x
-> These are the version of CARLA, more frequently updated and with the latest
-> features. Keep in mind that the API and features in this channel can (and
-> probably will) change.
+> Here are the previous versions of CARLA with links to the specific documentation for each version:
-- [CARLA 0.9.10](https://github.com/carla-simulator/carla/releases/tag/0.9.10)
-- [CARLA 0.9.9](https://github.com/carla-simulator/carla/releases/tag/0.9.9)
-- [CARLA 0.9.8](https://github.com/carla-simulator/carla/releases/tag/0.9.8)
-- [CARLA 0.9.7](https://github.com/carla-simulator/carla/releases/tag/0.9.7)
-- [CARLA 0.9.6](https://github.com/carla-simulator/carla/releases/tag/0.9.6)
-- [CARLA 0.9.5](https://github.com/carla-simulator/carla/releases/tag/0.9.5)
-- [CARLA 0.9.4](https://github.com/carla-simulator/carla/releases/tag/0.9.4)
-- [CARLA 0.9.3](https://github.com/carla-simulator/carla/releases/tag/0.9.3)
-- [CARLA 0.9.2](https://github.com/carla-simulator/carla/releases/tag/0.9.2)
-- [CARLA 0.9.1](https://github.com/carla-simulator/carla/releases/tag/0.9.1)
-- [CARLA 0.9.0](https://github.com/carla-simulator/carla/releases/tag/0.9.0)
-- [CARLA 0.8.4](https://github.com/carla-simulator/carla/releases/tag/0.8.4)
-- [CARLA 0.8.3](https://github.com/carla-simulator/carla/releases/tag/0.8.3)
+- [CARLA 0.9.11](https://github.com/carla-simulator/carla/releases/tag/0.9.11/) - [Documentation](https://carla.readthedocs.io/en/0.9.11/)
+- [CARLA 0.9.10](https://github.com/carla-simulator/carla/releases/tag/0.9.10/) - [Documentation](https://carla.readthedocs.io/en/0.9.10/)
+- [CARLA 0.9.9](https://github.com/carla-simulator/carla/releases/tag/0.9.9/) - [Documentation](https://carla.readthedocs.io/en/0.9.9/)
+- [CARLA 0.9.8](https://github.com/carla-simulator/carla/releases/tag/0.9.8/) - [Documentation](https://carla.readthedocs.io/en/0.9.8/)
+- [CARLA 0.9.7](https://github.com/carla-simulator/carla/releases/tag/0.9.7/) - [Documentation](https://carla.readthedocs.io/en/0.9.7/)
+- [CARLA 0.9.6](https://github.com/carla-simulator/carla/releases/tag/0.9.6/) - [Documentation](https://carla.readthedocs.io/en/0.9.6/)
+- [CARLA 0.9.5](https://github.com/carla-simulator/carla/releases/tag/0.9.5/) - [Documentation](https://carla.readthedocs.io/en/0.9.5/)
+- [CARLA 0.9.4](https://github.com/carla-simulator/carla/releases/tag/0.9.4/) - [Documentation](https://carla.readthedocs.io/en/0.9.4/)
+- [CARLA 0.9.3](https://github.com/carla-simulator/carla/releases/tag/0.9.3/) - [Documentation](https://carla.readthedocs.io/en/0.9.3/)
+- [CARLA 0.9.2](https://github.com/carla-simulator/carla/releases/tag/0.9.2/) - [Documentation](https://carla.readthedocs.io/en/0.9.2/)
+- [CARLA 0.9.1](https://github.com/carla-simulator/carla/releases/tag/0.9.1/) - [Documentation](https://carla.readthedocs.io/en/0.9.1/)
+- [CARLA 0.9.0](https://github.com/carla-simulator/carla/releases/tag/0.9.0/) - [Documentation](https://carla.readthedocs.io/en/0.9.0/)
-### Stable [[Documentation](https://carla.readthedocs.io/en/stable/)]
+### Versions 0.8.x
-> The most tested and robust release out there!
-
-- [CARLA 0.8.2](https://github.com/carla-simulator/carla/releases/tag/0.8.2)
+- [CARLA 0.8.4](https://github.com/carla-simulator/carla/releases/tag/0.8.4/) - [Documentation](https://carla.readthedocs.io/en/0.8.4/)
+- [CARLA 0.8.3](https://github.com/carla-simulator/carla/releases/tag/0.8.3/)
+- [CARLA 0.8.2](https://github.com/carla-simulator/carla/releases/tag/0.8.2/) - [Documentation](https://carla.readthedocs.io/en/stable/)
- - -
### Docker
-All the versions are also available to pull from DockerHub
+All versions are available to pull from DockerHub:
```sh
docker pull carlasim/carla:X.X.X
```
-Use tag "latest" for the nightly build
+Use tag "latest" for the most recent release:
```sh
docker pull carlasim/carla:latest
diff --git a/Docs/ecosys_ansys.md b/Docs/ecosys_ansys.md
new file mode 100644
index 000000000..22f3a38e9
--- /dev/null
+++ b/Docs/ecosys_ansys.md
@@ -0,0 +1,8 @@
+# Ansys Real Time Radar Model: Training a Vehicle Longitudinal Controller Using Reinforcement Learning
+
+In a webinair series in April 2021, [Ansys](https://www.ansys.com/) presented the details of their integration of the Ansys Real Time Radar (RTR) with the CARLA simulator. Here you can download and view the presentation slides and videos that accompanied the webinair.
+
+The presentation details how the RTR was integrated with CARLA to train a vehicle longitudinal controller using reinforcement learning and includes the model, action space and reward policy used. The videos show the results of the training in the CARLA simulator.
+
+View the presentation [here](https://drive.google.com/file/d/1xtGaI8Ls6C8Jh-PQvKRrLKs6c3ri3WQ2/view) and the videos [here](https://drive.google.com/file/d/1whHE1MKhzQtW3jj4dJCW6A3mCjUnNaJI/view).
+
diff --git a/Docs/extra.css b/Docs/extra.css
index d64c890d3..e05b7f95b 100644
--- a/Docs/extra.css
+++ b/Docs/extra.css
@@ -12,6 +12,13 @@
text-align: center;
}
+/************************* NAV BAR **************************/
+
+.caption {
+ /* background-color: #d6d6d6;
+ color: #404040; */
+ text-decoration: underline;
+}
/************************* DEFAULT TABLES **************************/
@@ -244,3 +251,18 @@ table tbody td{
top: 70px;
left: 1100px;
}
+
+/************************* LATEST WARNING BANNER **************************/
+
+.dev-version-warning {
+ padding-top: 15px;
+ padding-bottom: 15px;
+ padding-left: 15px;
+ padding-right: 15px;
+ margin-bottom: 8px;
+ color: #404040;
+ font-weight: bold;
+ background-color: #f55c47;
+ text-align: center;
+ border-radius: 5px;
+}
diff --git a/Docs/extra.js b/Docs/extra.js
new file mode 100644
index 000000000..58e37b47e
--- /dev/null
+++ b/Docs/extra.js
@@ -0,0 +1,9 @@
+$(document).ready(function () {
+ if(window.location.href.indexOf("/latest/") != -1) {
+ var banner = document.createElement("div");
+ var section = document.getElementsByClassName("section");
+ banner.className = "dev-version-warning";
+ banner.innerHTML = "You are currently reading documentation for the \"dev\" branch of CARLA. This documentation refers to features currently in development and may result in unexpected behaviour. To read documentation for previous releases, select the desired version in the bottom, right-hand corner of the screen.";
+ section[0].insertBefore(banner,section[0].childNodes[0]);
+ }
+});
\ No newline at end of file
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diff --git a/Docs/index.md b/Docs/index.md
index 1a3183709..5e101e925 100644
--- a/Docs/index.md
+++ b/Docs/index.md
@@ -1,28 +1,30 @@
# CARLA Documentation
-Welcome to the CARLA documentation.
+Welcome to the CARLA documentation.
-This home page contains an index with a brief description of the different sections in the documentation. Feel free to read in whatever order preferred. In any case, here are a few suggestions for newcomers.
+This home page contains an index with a brief description of the different sections in the documentation. Feel free to read in whatever order preferred. In any case, here are a few suggestions for newcomers.
-* __Install CARLA.__ Either follow the [Quick start installation](start_quickstart.md) to get a CARLA release or [make the build](build_linux.md) for a desired platform.
-* __Start using CARLA.__ The section titled [First steps](core_concepts.md) is an introduction to the most important concepts.
-* __Check the API.__ there is a handy [Python API reference](python_api.md) to look up the classes and methods available.
+* __Install CARLA.__ Either follow the [Quick start installation](start_quickstart.md) to get a CARLA release or [make the build](build_linux.md) for a desired platform.
+* __Start using CARLA.__ The section titled [First steps](core_concepts.md) is an introduction to the most important concepts.
+* __Check the API.__ there is a handy [Python API reference](python_api.md) to look up the classes and methods available.
-The CARLA forum is available to post any doubts or suggestions that may arise during the reading.
+The CARLA forum is available to post any doubts or suggestions that may arise during the reading.
+
+
!!! Warning
- Change the docs version to fit the CARLA version you are using. Use the pannel in the bottom-right side of this window to change to previous versions. 
+ __Change the docs version to fit the CARLA version you are using__. Use the panel in the bottom-right side of this window to change to previous versions. __The _Latest_ version points to documentation in the `dev` branch__ which may refer to features currently in development and __not available__ in any packaged version of CARLA, as well general documentation improvements. 
---
## Getting started
[__Introduction__](start_introduction.md) — What to expect from CARLA.
-[__Quick start__](start_quickstart.md) — Get the CARLA releases.
+[__Quick start package installation__](start_quickstart.md) — Get the CARLA releases.
## Building CARLA
@@ -31,7 +33,7 @@ CARLA forum
[__Windows build__](build_windows.md) — Make the build on Windows.
[__Update CARLA__](build_update.md) — Get up to date with the latest content.
[__Build system__](build_system.md) — Learn about the build and how it is made.
-[__Running in a Docker__](build_docker.md) — Run CARLA using a container solution.
+[__CARLA in Docker__](build_docker.md) — Run CARLA using a container solution.
[__F.A.Q.__](build_faq.md) — Some of the most frequent installation issues.
@@ -42,18 +44,25 @@ CARLA forum
[__3rd. Maps and navigation__](core_map.md) — Discover the different maps and how do vehicles move around.
[__4th. Sensors and data__](core_sensors.md) — Retrieve simulation data using sensors.
-## Advanced steps
+## Advanced concepts
[__OpenDRIVE standalone mode__](adv_opendrive.md) — Use any OpenDRIVE file as a CARLA map.
[__PTV-Vissim co-simulation__](adv_ptv.md) — Run a synchronous simulation between CARLA and PTV-Vissim.
[__Recorder__](adv_recorder.md) — Register the events in a simulation and play it again.
[__Rendering options__](adv_rendering_options.md) — From quality settings to no-render or off-screen modes.
[__RSS__](adv_rss.md) — An implementation of RSS in the CARLA client library.
-[__SUMO co-simulation__](adv_sumo.md) — Run a synchronous simulation between CARLA and SUMO.
[__Synchrony and time-step__](adv_synchrony_timestep.md) — Client-server communication and simulation time.
+[__Benchmarking Performance__](adv_benchmarking.md) — Perform benchmarking using our prepared script.
+[__CARLA Agents__](adv_agents.md) — Agents scripts allow single vehicles to roam the map or drive to a set destination.
+
+## Traffic Simulation
+
+[__ Traffic Simulation Overview__](ts_traffic_simulation_overview.md) — An overview of the different options available to populate your scenes with traffic
[__Traffic Manager__](adv_traffic_manager.md) — Simulate urban traffic by setting vehicles to autopilot mode.
+[__SUMO co-simulation__](adv_sumo.md) — Run a synchronous simulation between CARLA and SUMO.
+[__Scenic__](tuto_G_scenic.md) — Follow an example of defining different scenarios using the Scenic library.
## References
-[__Python API reference__](python_api.md) — Classes and methods in the Python API.
+[__Python API reference__](python_api.md) — Classes and methods in the Python API.
[__Blueprint library__](bp_library.md) — Blueprints provided to spawn actors.
[__C++ reference__](ref_cpp.md) — Classes and methods in CARLA C++.
[__Recorder binary file format__](ref_recorder_binary_file_format.md) — Detailed explanation of the recorder file format.
@@ -63,33 +72,56 @@ CARLA forum
[__carlaviz — web visualizer__](plugins_carlaviz.md) — Plugin that listens the simulation and shows the scene and some simulation data in a web browser.
## ROS bridge
-[__ROS bridge installation__](ros_installation.md) — The different ways to install the ROS bridge.
-[__CARLA messages reference__](ros_msgs.md) — Contains explanations and fields for every type of CARLA message available in ROS.
-[__Launchfiles reference__](ros_launchs.md) — Lists the launchfiles and nodes provided, and the topics being consumed and published.
+[__ROS bridge documentation__](ros_documentation.md) — Brief overview of the ROS bridge and a link to the full documentation
+## Custom Maps
+
+[__Overview of custom maps in CARLA__](tuto_M_custom_map_overview.md) — An overview of the process and options involved in adding a custom, standard sized map
+[__Create a map in RoadRunner__](tuto_M_generate_map.md) — How to generate a customs, standard sized map in RoadRunner
+[__ Import map in CARLA package__](tuto_M_add_map_package.md) How to import a map in a CARLA package
+[__Import map in CARLA source build__](tuto_M_add_map_source.md) — How to import a map in CARLA built from source
+[__Alternative ways to import maps__](tuto_M_add_map_alternative.md) — Alternative methods to import maps
+[__ Manually prepare map package__](tuto_M_manual_map_package.md) — How to prepare a map for manual import
+[__Customizing maps: Layered maps__](tuto_M_custom_layers.md) — How to create sub-layers in your custom map
+[__ Customizing maps: Traffic lights and signs__](tuto_M_custom_add_tl.md) — How to add traffic lights and signs to your custom map
+[__ Customizing maps: Road painter__](tuto_M_custom_road_painter.md) — How to use the road painter tool to change the apearance of the road
+[__Customizing Maps: Procedural Buildings__](tuto_M_custom_buildings.md) — Populate your custom map with buildings
+[__ Customizing maps: Weather and landscape__](tuto_M_custom_weather_landscape.md) — Create the weather profile for your custom map and populate the landscape
+[__Generate pedestrian navigation__](tuto_M_generate_pedestrian_navigation.md) — Obtain the information needed for walkers to move around.
+
+## Large Maps
+
+[__Large maps overview__](large_map_overview.md) — An explanation of how large maps work in CARLA
+[__Create a Large Map in RoadRunner__](large_map_roadrunner.md) — How to create a large map in RoadRunner
+[__Import/Package a Large Map__](large_map_import.md) — How to import a large map
## Tutorials — General
[__Add friction triggers__](tuto_G_add_friction_triggers.md) — Define dynamic box triggers for wheels.
[__Control vehicle physics__](tuto_G_control_vehicle_physics.md) — Set runtime changes on a vehicle physics.
[__Control walker skeletons__](tuto_G_control_walker_skeletons.md) — Animate walkers using skeletons.
+[__Generate maps with OpenStreetMap__](tuto_G_openstreetmap.md) — Use OpenStreetMap to generate maps for use in simulations.
[__Retrieve simulation data__](tuto_G_retrieve_data.md) — A step by step guide to properly gather data using the recorder.
+[__CarSim Integration (Beta)__](tuto_G_carsim_integration.md) — Tutorial on how to run a simulation using the CarSim vehicle dynamics engine.
+[__RLlib Integration__](tuto_G_rllib_integration.md) — Find out how to run your own experiment using the RLlib library.
+[__Chrono Integration__](tuto_G_chrono.md) — Use the Chrono integration to simulation physics
+[__Build Unreal Engine and CARLA in Docker__](build_docker_unreal.md) — Build Unreal Engine and CARLA in Docker
## Tutorials — Assets
-[__Add a new map__](tuto_A_add_map.md) — Create and ingest a new map.
[__Add a new vehicle__](tuto_A_add_vehicle.md) — Prepare a vehicle to be used in CARLA.
[__Add new props__](tuto_A_add_props.md) — Import additional props into CARLA.
[__Create standalone packages__](tuto_A_create_standalone.md) — Generate and handle standalone packages for assets.
-[__Map customization__](tuto_A_map_customization.md) — Edit an existing map.
[__Material customization__](tuto_A_material_customization.md) — Edit vehicle and building materials.
-[__Vehicle modelling__](tuto_A_vehicle_modelling.md) — Create a new vehicle for CARLA.
## Tutorials — Developers
-[__Contribute with new assets__](tuto_D_contribute_assets.md) — Add new content to CARLA.
+[__How to upgrade content__](tuto_D_contribute_assets.md) — Add new content to CARLA.
[__Create a sensor__](tuto_D_create_sensor.md) — Develop a new sensor to be used in CARLA.
+[__Create semantic tags__](tuto_D_create_semantic_tags.md) — Define customized tags for semantic segmentation.
[__Customize vehicle suspension__](tuto_D_customize_vehicle_suspension.md) — Modify the suspension system of a vehicle.
-[__Make a release__](tuto_D_make_release.md) — For developers who want to publish a release.
[__Generate detailed colliders__](tuto_D_generate_colliders.md) — Create detailed colliders for vehicles.
-[__Generate pedestrian navigation__](tuto_D_generate_pedestrian_navigation.md) — Obtain the information needed for walkers to move around.
+[__Make a release__](tuto_D_make_release.md) — How to make a release of CARLA
+## CARLA Ecosystem
+
+[__Ansys Real Time Radar Model__](ecosys_ansys.md) — Details about the Ansys RTR Webinair
## Contributing
[__Contribution guidelines__](cont_contribution_guidelines.md) — The different ways to contribute to CARLA.
[__Code of conduct__](cont_code_of_conduct.md) — Standard rights and duties for contributors.
diff --git a/Docs/large_map_import.md b/Docs/large_map_import.md
new file mode 100644
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+++ b/Docs/large_map_import.md
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+# Import/Package a Large Map
+
+Large maps generated in RoadRunner can be imported into the source build of CARLA and packaged for distribution and usage in a CARLA standalone package. The process is very simlar to that of standard maps with the addition of specific nomenclature for tiles and batch importing.
+
+- [__Files and folders__](#files-and-folders)
+- [__Create the JSON description (Optional)__](#create-the-json-description-optional)
+- [__Making the import__](#making-the-import)
+- [__Package a large map__](#package-a-large-map)
+
+---
+
+## Files and folders
+
+All files to be imported should be placed in the `Import` folder of the root CARLA directory. These files should include:
+
+- The mesh of the map in multiple `.fbx` files representing different tiles of the map.
+- The OpenDRIVE definition in a single `.xodr` file.
+
+!!! Warning
+ You cannot import large maps and standard maps at the same time.
+
+The naming convention of map tiles is very important. Each map tile should be named according to the following convention:
+
+```
+
_Tile__.fbx
+```
+
+Be aware that a more positive __y coordinate__ refers to a tile lower on the y-axis. For example,`Map01_Tile_0_1` would sit just below `Map01_Tile_0_0`.
+
+>>>>>>>>
+
+A resulting `Import` folder with a package containing a large map made of four tiles should have a structure similar to the one below:
+
+```sh
+Import
+│
+└── Package01
+ ├── Package01.json
+ ├── Map01_Tile_0_0.fbx
+ ├── Map01_Tile_0_1.fbx
+ ├── Map01_Tile_1_0.fbx
+ ├── Map01_Tile_1_1.fbx
+ └── Map01.xodr
+
+```
+
+!!! Note
+ The `package.json` file is not strictly necessary. If there is no `package.json` file created, the automated import process will create one. Find out more about to structure your own `package.json` in the next section.
+
+---
+
+## Create the JSON description (Optional)
+
+The `.json` description is created automatically during the import process, but there is also the option to create one manually. An existing `.json` description will override any values passed as arguments in the import process.
+
+The `.json` file should be created in the root folder of the package. The file name will be the package distribution name. The content of the file describes a JSON array of __maps__ and __props__ with basic information for each one.
+
+__Maps__ need the following parameters:
+
+- __name:__ Name of the map. This must be the same as the `.fbx` and `.xodr` files.
+- __xodr:__ Path to the `.xodr` file.
+- __use_carla_materials:__ If __True__, the map will use CARLA materials. Otherwise, it will use RoadRunner materials.
+- __tile_size:__ The size of the tiles. Default value is 2000 (2kmx2km).
+- __tiles:__ A list of the `.fbx` tile files that make up the entire map.
+
+__Props__ are not part of this tutorial. Please see [this](tuto_A_add_props.md) tutorial for how to add new props.
+
+The resulting `.json` file should resemble the following:
+
+```json
+{
+ "maps": [
+ {
+ "name": "Map01",
+ "xodr": "./Map01.xodr",
+ "use_carla_materials": true,
+ "tile_size": 2000,
+ "tiles": [
+ "./Map01_Tile_0_0.fbx",
+ "./Map01_Tile_0_1.fbx",
+ "./Map01_Tile_1_0.fbx",
+ "./Map01_Tile_1_1.fbx"
+ ]
+ }
+ ],
+ "props": []
+}
+```
+
+
+
+---
+
+## Making the import
+
+When all files have been placed in the `Import` folder, run the following command in the root CARLA folder:
+
+```sh
+make import
+```
+
+Depending on your system, Unreal Engine may consume too much memory to be able to import all files at once. You can choose to import the files in batches of MB by running the command:
+
+```sh
+make import ARGS="--batch-size=200"
+```
+
+Two more flags exist for the `make import` command:
+
+- `--package=` specifies the name of the package. By default, this is set to `map_package`. Two packages cannot have the same name, so using the default value will lead to errors on a subsequent ingestion. __It is highly recommended to change the name of the package__. Use this flag by running the command:
+
+```sh
+make import ARGS="--package="
+```
+
+- `--no-carla-materials` specifies that you do not want to use the default CARLA materials (road textures etc). You will use the RoadRunner materials instead. This flag is __only required if you are not__ providing your own [`.json` file](tuto_M_manual_map_package.md). Any value in the `.json` file will override this flag. Use this flag by running the command:
+
+```sh
+make import ARGS="--no-carla-materials"
+```
+
+All files will be imported and prepared to be used in the Unreal Editor. The map package will be created in `Unreal/CarlaUE4/Content`. A base map tile, ``, will be created as a streaming level for all the tiles. The base tile will contain the sky, weather, and large map actors and will be ready for use in a simulation.
+
+!!! Note
+ It is currently not recommended to use the customization tools provided for standard maps in the Unreal Editor, e.g., road painter, procedural buildings, etc.
+
+---
+
+## Package a large map
+
+To package your large map so it can be used in the CARLA standalone package, run the following command:
+
+```sh
+make package ARGS="--packages="
+```
+
+This will create a standalone package compressed in a `.tar.gz` file. The files will be saved in the `Dist` folder on Linux, and `/Build/UE4Carla/` on Windows. They can then be distributed and packaged to use in standalone CARLA packages.
+
+---
+
+If you have any questions about the large map import and packaging process, then you can ask in the [forum](https://github.com/carla-simulator/carla/discussions).
+
+