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.
__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.
*`reload_world()` creates a new instance of the world with the same map.
*`load_world()` changes the current map and creates a new world.
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.
*__[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.
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 can be accessed through [__carla.LaneMarking__](python_api.md#carla.LaneMarking). These are defined with a series of variables.
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.
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.
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.
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.
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.
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]:
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.
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.
*`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.
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 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.
* __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.
* __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.
* __Convert simulation point to geographical coordinates.__ Transforms a certain location to a [carla.GeoLocation](python_api.md#carla.GeoLocation) with latitude and longitude values.
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:
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.
| **[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**](<https://en.wikipedia.org/wiki/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.|
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. Layered maps can be idenitified 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:
