Operational Guide¶

This guide provides step-by-step instructions on how to run, customize, and analyze simulations using the CARLA and SUMO co-simulation environment.

Running a Basic Simulation¶

Start CARLA Server:

Before running any simulation, ensure the CARLA server is up and running:
```
cd ~/carla
./CarlaUE4.sh -quality-level=Epic
```
Leave this terminal open as the CARLA server will continue to run in the background.
Prepare SUMO Scenario:

Navigate to the directory containing the SUMO scenario files:
```
cd ~/sumo-carla-co-simulation/scenarios
```
Edit the SUMO configuration file (.sumocfg) to customize traffic settings if needed.
Run Co-Simulation:

Execute the co-simulation script:
```
python3 run_co_simulation.py --scenario scenarios/sumo_scenario.sumocfg
```
Monitor the output in the terminal for any errors or warnings.

Modify SUMO Configuration:

The SUMO configuration file (.sumocfg) controls various aspects of the simulation, such as traffic density, traffic lights, and routes. Edit this file to:
- Adjust traffic flow.
- Change vehicle types.
- Modify traffic signal timings.
Edit CARLA Scenario:

CARLA scenarios are defined in Python scripts that control the environment, weather, and vehicle behavior. Customize these scripts by editing:
- Weather conditions (carla.WeatherParameters).
- Spawn locations for vehicles and pedestrians.
- Sensor configurations for autonomous vehicles.
Combine Custom Scenarios:

You can combine custom SUMO and CARLA scenarios by ensuring the SUMO network aligns with the CARLA map. Use the osmWebWizard.py in SUMO to generate compatible road networks.

Data Logging:

Both CARLA and SUMO can log data during the simulation. Ensure that logging is enabled:
- For SUMO, use the –summary-output option in the .sumocfg file.
- For CARLA, modify the Python script to save sensor data and vehicle trajectories.
Visualization:

Use tools like SUMO-GUI to visualize traffic flow and inspect vehicle interactions. CARLA’s built-in visualization tools allow you to replay scenarios and inspect sensor data.
Post-Processing:

Analyze the recorded data using Python or MATLAB for:
- Vehicle trajectories.
- Collision detection.
- Traffic flow analysis.
Generate plots and reports based on simulation results.

CARLA Server Crashes: Ensure your GPU drivers are up to date and that your system has enough resources to handle high-fidelity simulations.
SUMO Traffic Issues: Double-check the road network and vehicle routes in the SUMO configuration file for any inconsistencies.
Synchronization Issues: If the co-simulation seems out of sync, adjust the time step configurations in both SUMO and CARLA to ensure they match.