cleanup code + fix missing dois

Author: david-gasinski

cawsr.py

@@ -27,6 +27,7 @@
 from typing import Optional, Union, Callable
 
 from srunner.scenariomanager.scenario_manager import ScenarioManager
+from srunner.scenariomanager.timer import GameTime
 from srunner.tools.results_manager import ScenarioDefinitionManager
 from srunner.scenarios.route_scenario import RouteScenario
 from srunner.scenariomanager.carla_data_provider import CarlaDataProvider
@@ -86,7 +87,7 @@ def __init__(self, cawsr_config: dict, carla_conf: CARLA) -> None:
         # manages results directories
         self.results_manager = ScenarioDefinitionManager()
 
-        #  capture SIGINT for cleanp
+        #  capture SIGINT for cleanup
         self._shutdown_requested = False
 
         if sys.platform != "win32":
@@ -163,7 +164,8 @@ def run_scenario(
         self.ego_vehicles.append(actor)
         logger.info(f"Spawned ego with id: {actor.id}")
 
-        self.carla_world.tick()  # client must tick to spawn actors
+        # client must tick to spawn actors
+        self._tick_carla()
 
         logger.info("Initialising Autoware...")
         agent_class_name = self.module_aw_agent.__name__.title().replace("_", "")
@@ -188,7 +190,7 @@ def run_scenario(
 
         ego.prepare_ego(route[0][0])  # set location to first waypoint
 
-        self.carla_world.tick()
+        self._tick_carla()
 
         logger.info("Loading Traffic Manager...")
         tm_port = int(self._carla.TRAFFIC_MANAGER.PORT)  # type: ignore
@@ -265,6 +267,18 @@ def run_scenario(
 
         result_.put(result_dict)
 
+    def _tick_carla(self) -> None:
+        timestamp = None
+        world = CarlaDataProvider.get_world()
+        if world:
+            snapshot = world.get_snapshot()
+            if snapshot:
+                timestamp = snapshot.timestamp
+        if timestamp:
+            CarlaDataProvider.get_world().tick()
+            CarlaDataProvider.on_carla_tick()
+            GameTime.on_carla_tick(timestamp)
+
     def _load_alg(self) -> type[BasicAlgorithm]:
         """Load an algorithm instance from mounted docker volume algorithms/
 
@@ -285,10 +299,12 @@ def _load_alg(self) -> type[BasicAlgorithm]:
         )
 
     def run_algorithm(self) -> None:
-        """Executes CAWSR in algorithm mode. Every scenario"""
+        """Executes CAWSR in algorithm mode"""
+
         # load the algorithm and scenario defintion
         optimisation_algorithm = self._load_alg()
         scenario = pathlib.Path(self._conf["algorithm"]["initial_definition"])
+
         # add some code here
         # if scenario = null (initial definition not given)
         # run the algorithm to generate a new, random scenario
@@ -317,7 +333,7 @@ def run_algorithm(self) -> None:
                 self.results_manager.last_scenario, env_config
             )[
                 0
-            ]  # route id. Multiple routes currently aren't supported, so use first route
+            ]  # route id. Multiple routes currently aren't supported, so use first route -> fix to use config
 
             json_definition = self._cawsr_process(
                 route_config=route_config,

paper.bib

@@ -9,6 +9,7 @@ @inproceedings{carla_sim
 @inproceedings{osikowicz2025empirically,
   title        = {Empirically evaluating flaky tests for autonomous driving systems in simulated environments},
   author       = {Osikowicz, Olek and McMinn, Phil and Shin, Donghwan},
+  doi          = {10.1109/FTW66604.2025.00009},
   booktitle    = {2025 IEEE/ACM International Flaky Tests Workshop (FTW)},
   pages        = {13--20},
   year         = {2025},
@@ -18,6 +19,7 @@ @inproceedings{osikowicz2025empirically
 @article{Jaeger2023ICCV,
   title     = {Hidden Biases of End-to-End Driving Models},
   author    = {Bernhard Jaeger and Kashyap Chitta and Andreas Geiger},
+  doi       = {10.1109/iccv51070.2023.00757},
   booktitle = {Proc. of the IEEE International Conf. on Computer Vision (ICCV)},
   year      = {2023}
 }
@@ -26,6 +28,7 @@ @inproceedings{kato2018autoware
   title        = {Autoware on board: Enabling autonomous vehicles with embedded systems},
   author       = {Kato, Shinpei and Tokunaga, Shota and Maruyama, Yuya and Maeda, Seiya and Hirabayashi, Manato and Kitsukawa, Yuki and Monrroy, Abraham and Ando, Tomohito and Fujii, Yusuke and Azumi, Takuya},
   booktitle    = {2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)},
+  doi          = {10.1109/iccps.2018.00035},
   pages        = {287--296},
   year         = {2018},
   organization = {IEEE}
@@ -74,6 +77,7 @@ @article{carlaautowarebridge
 @inproceedings{tehrani2025pcla,
   title     = {PCLA: A Framework for Testing Autonomous Agents in the CARLA Simulator},
   author    = {Tehrani, Masoud Jamshidiyan and Kim, Jinhan and Tonella, Paolo},
+  doi       = {10.1145/3696630.3728577},
   booktitle = {Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering},
   pages     = {1040--1044},
   year      = {2025}
@@ -131,8 +135,8 @@ @article{tang2023survey
 
 @ARTICLE{9793395,
   author={Chance, Greg and Ghobrial, Abanoub and McAreavey, Kevin and Lemaignan, Séverin and Pipe, Tony and Eder, Kerstin},
-  journal={IEEE Transactions on Intelligent Transportation Systems}, 
-  title={On Determinism of Game Engines Used for Simulation-Based Autonomous Vehicle Verification}, 
+  journal={IEEE Transactions on Intelligent Transportation Systems},
+  title={On Determinism of Game Engines Used for Simulation-Based Autonomous Vehicle Verification},
   year={2022},
   volume={23},
   number={11},
@@ -142,8 +146,8 @@ @ARTICLE{9793395
 
   @INPROCEEDINGS{9294422,
   author={Rong, Guodong and Shin, Byung Hyun and Tabatabaee, Hadi and Lu, Qiang and Lemke, Steve and Možeiko, Mārtiņš and Boise, Eric and Uhm, Geehoon and Gerow, Mark and Mehta, Shalin and Agafonov, Eugene and Kim, Tae Hyung and Sterner, Eric and Ushiroda, Keunhae and Reyes, Michael and Zelenkovsky, Dmitry and Kim, Seonman},
-  booktitle={2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, 
-  title={LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving}, 
+  booktitle={2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)},
+  title={LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving},
   year={2020},
   volume={},
   number={},

srunner/autoagents/autoware_carla_interface/carla_ros.py

@@ -14,7 +14,6 @@
 
 import json
 import math
-import time
 
 # pylint: disable=import-error
 from autoware_vehicle_msgs.msg import ControlModeReport
@@ -475,6 +474,12 @@ def ego_status(self):
     def run_step(self, input_data, timestamp):
         self.timestamp = timestamp
 
+        seconds = int(self.timestamp)
+        nanoseconds = int((self.timestamp - int(self.timestamp)) * 1000000000.0)
+        obj_clock = Clock()
+        obj_clock.clock = Time(sec=seconds, nanosec=nanoseconds)
+        self.clock_publisher.publish(obj_clock)
+
         # publish data of all sensors
         for key, data in input_data.items():
             sensor_type = self.id_to_sensor_type_map[key]
@@ -489,16 +494,7 @@ def run_step(self, input_data, timestamp):
             else:
                 self.ros2_node.get_logger().info("No Publisher for [{key}] Sensor")
 
-        time.sleep(0.05)  # 50ms delay to ensure published messages are received
-
-        seconds = int(self.timestamp)
-        nanoseconds = int((self.timestamp - int(self.timestamp)) * 1000000000.0)
-        obj_clock = Clock()
-        obj_clock.clock = Time(sec=seconds, nanosec=nanoseconds)
-        self.clock_publisher.publish(obj_clock)
-
         self.ego_status()
-
         return self.current_control
 
     def shutdown(self):

srunner/scenariomanager/scenario_manager.py

@@ -178,22 +178,18 @@ def _tick_scenario(self, timestamp):
             if self._debug_mode:
                 print("\n--------- Tick ---------\n")
 
-            
+            if self._agent is not None:
+                self._agent()  # pylint: disable=not-callable
 
             _tick_carla_start = time.perf_counter_ns() / 1e6
             if self._sync_mode and self._watchdog.get_status():
                 CarlaDataProvider.get_world().tick()
+                GameTime.on_carla_tick(timestamp)
+                CarlaDataProvider.on_carla_tick()
 
             MetricsCollector.update_key(
                 "carla_time", (time.perf_counter_ns() / 1e6) - _tick_carla_start
             )
-            
-            if self._agent is not None:
-                self._agent()  # pylint: disable=not-callable
-
-            # Update game time and actor information
-            GameTime.on_carla_tick(timestamp)
-            CarlaDataProvider.on_carla_tick()
 
             # Tick scenario
             _scenario_tick_start = time.perf_counter_ns() / 1e6