Merge branch 'master' into feature/new_tags_support

Docs/CHANGELOG.md

@@ -23,6 +23,7 @@
     - Added story support for `TrafficSignalControllerAction`
     - Added both init and story support for `LateralDistanceAction`
     - Added support for `TrafficSignalControllerCondition`
+* Supported OpenSCENARIO 2.0 standard.
 
 ### :bug: Bug Fixes
 * Fixed bug at OtherLeadingVehicle scenario causing the vehicles to move faster than intended

Docs/README_OpenSCENARIO_2.0.md

@@ -0,0 +1,123 @@
+# osc2-runner
+
+We use OpenScenario 2.0 as the scenario description language specification to design and implement the corresponding compilation system, which can automatically convert the test scenario described with OpenScenario 2.0 into a test scenario based on scenario runner, so as to use carla for autonomous driving testing.
+
+## Installation
+
+**1. Install JDK**
+
+```
+sudo apt install openjdk-17-jdk
+```    
+Confirm installation:
+```
+$ java -version
+```
+Output:
+```
+openjdk version "17.0.5" 2022-10-18
+OpenJDK Runtime Environment (build 17.0.5+8-Ubuntu-2ubuntu120.04)
+OpenJDK 64-Bit Server VM (build 17.0.5+8-Ubuntu-2ubuntu120.04, mixed mode, sharing)
+```
+
+**3、Install Antlr 4.10.1**
+
+```
+sudo apt install curl
+curl -O https://www.antlr.org/download/antlr-4.10.1-complete.jar
+```
+
+Put the .jar file into local/lib
+```
+$ sudo cp antlr-4.10.1-complete.jar /usr/local/lib/
+```
+
+The following three steps are used to configure environment variables and create aliases so that antlr4 can be easily used from the command line.
+```
+$ sudo gedit ~/.bashrc
+```
+Add the following at the end:
+```
+export CLASSPATH=".:/usr/local/lib/antlr-4.10.1-complete.jar:$CLASSPATH"
+alias antlr4='java -jar /usr/local/lib/antlr-4.10.1-complete.jar'
+alias grun='java org.antlr.v4.gui.TestRig'
+```
+And then:
+```
+source ~/.bashrc
+```
+
+Enter antlr4 for verifying in the terminal:
+```
+$ antlr4
+ANTLR Parser Generator  Version 4.10.1
+ -o ___              specify output directory where all output is generated
+ -lib ___            specify location of grammars, tokens files
+ -atn                generate rule augmented transition network diagrams
+ -encoding ___       specify grammar file encoding; e.g., euc-jp
+ -message-format ___ specify output style for messages in antlr, gnu, vs2005
+ -long-messages      show exception details when available for errors and warnings
+ -listener           generate parse tree listener (default)
+ -no-listener        don't generate parse tree listener
+ -visitor            generate parse tree visitor
+ -no-visitor         don't generate parse tree visitor (default)
+ -package ___        specify a package/namespace for the generated code
+ -depend             generate file dependencies
+ -D<option>=value    set/override a grammar-level option
+ -Werror             treat warnings as errors
+ -XdbgST             launch StringTemplate visualizer on generated code
+ -XdbgSTWait         wait for STViz to close before continuing
+ -Xforce-atn         use the ATN simulator for all predictions
+ -Xlog               dump lots of logging info to antlr-timestamp.log
+ -Xexact-output-dir  all output goes into -o dir regardless of paths/package
+```
+
+**4、Install antlr4 runtime**
+```
+pip install antlr4-python3-runtime==4.10
+```
+
+**5、Install python dependency**
+```
+pip install -r requirements.txt
+```
+
+**6.Install graphviz**
+
+```
+sudo apt-get install graphviz
+```
+
+
+**7、Configurate carla**
+
+(1) Download [carla release](https://carla-releases.s3.eu-west-3.amazonaws.com/Linux/CARLA_0.9.13.tar.gz)
+
+
+(2) Extract the carla installation package to a directory.
+
+On Ubuntu systems, the Carla environment variable is configured as follows:
+```bash
+export CARLA_ROOT=/home/dut-aiid/CARLA_0.9.13
+export PYTHONPATH=$PYTHONPATH:${CARLA_ROOT}/PythonAPI/carla/dist/carla-0.9.13-py3.7-linux-x86_64.egg:${CARLA_ROOT}/PythonAPI/carla/agents:${CARLA_ROOT}/PythonAPI/carla/agents/navigation:${CARLA_ROOT}/PythonAPI/carla:${CARLA_ROOT}/PythonAPI/examples:${CARLA_ROOT}/PythonAPI
+```
+
+## Quickstart
+
+**1、Run carla**
+
+```bash
+cd /home/xxx/CARLA_0.9.13
+./CarlaUE4.sh
+```
+
+**2、Start manual_control**
+
+```
+python manual_control.py -a --rolename=ego_vehicle
+```
+
+**3、Run a OpenSCENARIO 2.0 scenario**
+```
+python scenario_runner.py --sync  --openscenario2 srunner/examples/cut_in_and_slow_right.osc --reloadWorld 
+```

Docs/getting_scenariorunner.md

@@ -179,6 +179,24 @@ set PYTHONPATH=%PYTHONPATH%;%CARLA_ROOT%\PythonAPI\carla
 
 To permanently set the environment variables, go to *edit the environment variables of this account*. This can be quickly accessed by writing *env* on the Windows' search panel.
 
+If you need to run the scenario based on the OpenSCENARIO 2.0 format, please install graphviz and antlr first:
+```
+sudo apt-get install -y openjdk-17-jdk graphviz
+curl -O https://www.antlr.org/download/antlr-4.10.1-complete.jar
+sudo cp antlr-4.10.1-complete.jar /usr/local/lib/
+sudo gedit ~/.bashrc
+```
+Add environment variables into ~/.bashrc:
+```
+export CLASSPATH=".:/usr/local/lib/antlr-4.10.1-complete.jar:$CLASSPATH"
+alias antlr4='java -jar /usr/local/lib/antlr-4.10.1-complete.jar'
+alias grun='java org.antlr.v4.gui.TestRig'
+```
+And make the changes into effect:
+```
+source ~/.bashrc
+```
+
 ---
 ## Run a test 
 

Docs/getting_started.md

@@ -90,6 +90,19 @@ python scenario_runner.py --openscenario <path/to/xosc-file>
 Please note that the OpenSCENARIO support and the OpenSCENARIO format itself are still work in progress.
 More information you can find in [OpenSCENARIO support](openscenario_support.md)
 
+## Running scenarios using the OpenSCENARIO 2.0 format
+To run a scenario, which is based on the OpenSCENARIO 2.0 format, please run the ScenarioRunner as follows:
+```
+python scenario_runner.py --openscenario2 <path/to/osc-file>
+```
+
+To control the ego vehicle within the scenario or observe it, open another terminal and run:
+```
+python manual_control.py -a --rolename=ego_vehicle
+```
+
+For more information about how to run a OpenSCENARIO 2.0 scenario, please refer to [README_OpenSCENARIO_2.0](README_OpenSCENARIO_2.0.md)
+
 ### Running scenarios using the OpenSCENARIO format with Global ParameterDeclaration overwrite
 ```
 python scenario_runner.py --openscenario <path/to/xosc-file> --openscenarioparams 'param1: value1, param2: value2'

README.md

@@ -9,7 +9,7 @@ for CARLA. It also allows the execution of a simulation of the CARLA Challenge.
 You can use this system to prepare your agent for the CARLA Challenge.
 
 Scenarios can be defined through a Python interface, and with the newest version
-the scenario_runner also the upcoming [OpenSCENARIO](http://www.openscenario.org/) standard is supported.
+the scenario_runner also the upcoming [OpenSCENARIO](http://www.openscenario.org/) standard and [OpenSCENARIO 2.0](https://www.asam.net/standards/detail/openscenario/v200/) standard is supported.
 
 [![Scenario_Runner for CARLA](Docs/img/scenario_runner_video.png)](https://youtu.be/ChmF8IFagpo?t=68)
 

manual_control.py

@@ -133,12 +133,12 @@ def __init__(self, carla_world, hud, args):
         self.imu_sensor = None
         self.radar_sensor = None
         self.camera_manager = None
-        self.restart()
+        self.restart(args)
         self.world.on_tick(hud.on_world_tick)
         self.recording_enabled = False
         self.recording_start = 0
 
-    def restart(self):
+    def restart(self, args):
 
         if self.restarted:
             return
@@ -157,7 +157,7 @@ def restart(self):
             time.sleep(1)
             possible_vehicles = self.world.get_actors().filter('vehicle.*')
             for vehicle in possible_vehicles:
-                if vehicle.attributes['role_name'] == 'hero':
+                if vehicle.attributes['role_name'] == args.rolename:
                     print("Ego vehicle found")
                     self.player = vehicle
                     break
@@ -907,7 +907,7 @@ def game_loop(args):
         pygame.display.flip()
 
         hud = HUD(args.width, args.height)
-        world = World(sim_world, hud, args)
+        world = World(client.get_world(), hud, args)
         controller = KeyboardControl(world, args.autopilot)
 
         sim_world.wait_for_tick()

requirements.txt

@@ -10,3 +10,5 @@ numpy
 matplotlib
 six
 simple-watchdog-timer
+antlr4-python3-runtime==4.10
+graphviz

scenario_runner.py

@@ -39,6 +39,9 @@
 from srunner.scenarios.route_scenario import RouteScenario
 from srunner.tools.scenario_parser import ScenarioConfigurationParser
 from srunner.tools.route_parser import RouteParser
+from srunner.tools.osc2_helper import OSC2Helper
+from srunner.scenarios.osc2_scenario import OSC2Scenario
+from srunner.scenarioconfigs.osc2_scenario_configuration import OSC2ScenarioConfiguration
 
 # Version of scenario_runner
 VERSION = '0.9.13'
@@ -89,7 +92,6 @@ def __init__(self, args):
         # requests in the localhost at port 2000.
         self.client = carla.Client(args.host, int(args.port))
         self.client.set_timeout(self.client_timeout)
-
         dist = pkg_resources.get_distribution("carla")
         if LooseVersion(dist.version) < LooseVersion('0.9.12'):
             raise ImportError("CARLA version 0.9.12 or newer required. CARLA version found: {}".format(dist))
@@ -133,6 +135,9 @@ def _signal_handler(self, signum, frame):
         self._shutdown_requested = True
         if self.manager:
             self.manager.stop_scenario()
+            self._cleanup()
+            if not self.manager.get_running_status():
+                raise RuntimeError("Timeout occurred during scenario execution")
 
     def _get_scenario_class_or_fail(self, scenario):
         """
@@ -209,6 +214,7 @@ def _prepare_ego_vehicles(self, ego_vehicles):
                 self.ego_vehicles.append(CarlaDataProvider.request_new_actor(vehicle.model,
                                                                              vehicle.transform,
                                                                              vehicle.rolename,
+                                                                             random_location=vehicle.random_location,
                                                                              color=vehicle.color,
                                                                              actor_category=vehicle.category))
         else:
@@ -387,6 +393,12 @@ def _load_and_run_scenario(self, config):
                 scenario = RouteScenario(world=self.world,
                                          config=config,
                                          debug_mode=self._args.debug)
+            elif self._args.openscenario2:
+                scenario = OSC2Scenario(world=self.world,
+                                        ego_vehicles=self.ego_vehicles,
+                                        config=config,
+                                        osc2_file=self._args.openscenario2,
+                                        timeout=100000)
             else:
                 scenario_class = self._get_scenario_class_or_fail(config.type)
                 scenario = scenario_class(self.world,
@@ -498,6 +510,24 @@ def _run_openscenario(self):
         self._cleanup()
         return result
 
+    def _run_osc2(self):
+        """
+        Run a scenario based on ASAM OpenSCENARIO 2.0.
+        https://www.asam.net/static_downloads/public/asam-openscenario/2.0.0/welcome.html
+        """
+        # Load the scenario configurations provided in the config file
+        if not os.path.isfile(self._args.openscenario2):
+            print("File does not exist")
+            self._cleanup()
+            return False
+
+        config = OSC2ScenarioConfiguration(self._args.openscenario2, self.client)
+
+        result = self._load_and_run_scenario(config)
+        self._cleanup()
+
+        return result
+
     def run(self):
         """
         Run all scenarios according to provided commandline args
@@ -507,6 +537,8 @@ def run(self):
             result = self._run_openscenario()
         elif self._args.route:
             result = self._run_route()
+        elif self._args.openscenario2:
+            result = self._run_osc2()
         else:
             result = self._run_scenarios()
 
@@ -543,6 +575,7 @@ def main():
         '--scenario', help='Name of the scenario to be executed. Use the preposition \'group:\' to run all scenarios of one class, e.g. ControlLoss or FollowLeadingVehicle')
     parser.add_argument('--openscenario', help='Provide an OpenSCENARIO definition')
     parser.add_argument('--openscenarioparams', help='Overwrited for OpenSCENARIO ParameterDeclaration')
+    parser.add_argument('--openscenario2', help='Provide an openscenario2 definition')
     parser.add_argument(
         '--route', help='Run a route as a scenario (input: (route_file,scenario_file,[route id]))', nargs='+', type=str)
 
@@ -571,12 +604,14 @@ def main():
     arguments = parser.parse_args()
     # pylint: enable=line-too-long
 
+    OSC2Helper.wait_for_ego = arguments.waitForEgo
+
     if arguments.list:
         print("Currently the following scenarios are supported:")
         print(*ScenarioConfigurationParser.get_list_of_scenarios(arguments.configFile), sep='\n')
         return 1
 
-    if not arguments.scenario and not arguments.openscenario and not arguments.route:
+    if not arguments.scenario and not arguments.openscenario and not arguments.route and not arguments.openscenario2:
         print("Please specify either a scenario or use the route mode\n\n")
         parser.print_help(sys.stdout)
         return 1

srunner/autoagents/npc_agent.py

@@ -57,9 +57,7 @@ def sensors(self):
         return sensors
 
     def run_step(self, input_data, timestamp):
-        """
-        Execute one step of navigation.
-        """
+        # Execute one step of navigation.
         if not self._agent:
 
             # Search for the ego actor

srunner/examples/acceleration.osc

@@ -0,0 +1,34 @@
+import basic.osc
+
+type acceleration is SI(m: 1, s: -2)
+unit kphps               of acceleration is SI(m: 1, s: -1, factor: 0.277777778)
+
+scenario top:
+    path: Path                      # A path in the map
+    path.set_map("Town04")    # specify map to use in this test
+    path.path_min_driving_lanes(2)         # Path should have at least two lanes
+
+    ego_vehicle: Model3                # ego car
+    npc: Rubicon               # The other car
+
+    event start
+    event end
+    do serial:
+        get_ahead: parallel(duration: 15s):
+            ego_vehicle.drive(path) with:
+                speed(30kph)
+                lane(1, at: start) # left to right: [1..n]
+            npc.drive(path) with:
+                lane(right_of: ego_vehicle, at: start)
+                position(15m, behind: ego_vehicle, at: start)
+                position(20m, ahead_of: ego_vehicle, at: end)       
+
+        slow: parallel(duration: 10s):
+            ego_vehicle.drive(path)
+            npc.drive(path) with:
+                speed(10kph)
+
+        accelerate: parallel(duration: 13s):
+            ego_vehicle.drive(path)
+            npc.drive(path) with:
+                acceleration(15kphps)