ADORe and SUMO

This document describes how to get ADORe and SUMO running together using the sumo_bridge ROS 2 node.

sumo_bridge ROS 2 node

The sumo_bridge is a ROS 2 node located in ros2_workspace/src/adore_interfaces/sumo_bridge that bridges SUMO traffic simulation to the ADORe stack via libsumo. SUMO vehicles are published as TrafficParticipantSet messages and the ego vehicle state is injected back into SUMO each simulation step.

Quick Start

Prerequisites

ADORe built: make build
Lichtblick running: cd tools/Lichtblick && make start

1. Start an interactive ADORe CLI session

make cli

2. Navigate to the simulation scenarios directory

cd adore_scenarios/simulation_scenarios

3. Launch a SUMO scenario

For the synthetic 50 m circle track:

ros2 launch sumo_test.launch.py

For the georeferenced OSM scenario with live traffic:

ros2 launch sumo_example.launch.py

4. Open Lichtblick in a Chromium-based browser Open http://localhost:8080/?ds=rosbridge-websocket&ds.url=ws://localhost:9090&layout=Default.json in a Chromium-based browser.

Configuration via Environmental Variables

All variables are set in adore.env.

Variable	Default	Description
`SUMO_BRIDGE_ENABLE`	`false`	Set to `true` to start the bridge
`SUMO_CONFIG_DIRECTORY`	`ros2_workspace/src/adore_interfaces/sumo_bridge/sumo_configs`	Path relative to `SOURCE_DIRECTORY` containing `.sumocfg` files
`SUMO_BRIDGE_CONFIG_FILE`	`demo_sumo_bridge.sumocfg`	Config filename. Sets `SUMO_CONFIG_FILE` in `adore.env`
`SUMO_HOME`	`/usr/share/sumo`	Path to SUMO installation

ROS Parameters

Parameter	Type	Default	Description
`sumo_config_file`	`string`	`""`	Absolute path to the `.sumocfg` file. Required.
`sumo_step_length`	`double`	`0.05`	SUMO simulation step length in seconds
`use_gui`	`bool`	`false`	Launch `sumo-gui` instead of headless `sumo`. Starts immediately without requiring the play button.
`gui_settings_file`	`string`	`""`	Path to a SUMO GUI settings XML file
`gui_zoom`	`double`	`5000.0`	Initial zoom level for `sumo-gui` (percentage; 5000 ≈ 10 m street level)
`gui_follow_ego`	`bool`	`true`	Whether `sumo-gui` tracks and follows the ego vehicle
`ego_start_position`	`string`	`""`	Ego start position as `"lat,lon,psi"` (psi in radians CCW from east). Derives UTM zone/letter and SUMO coordinates automatically. Required for georeferenced scenarios; omit for local coordinate scenarios.
`ego_tracking_id`	`int`	`0`	Tracking ID of the ego vehicle, used for GUI follow and color assignment
`ego_vehicle_color`	`string`	`"255,255,0"`	Ego vehicle color as `"R,G,B"` or `"R,G,B,A"` with values 0–255
`utm_zone`	`int`	`32`	UTM zone number. Used only when `ego_start_position` is not set.
`utm_letter`	`string`	`"U"`	UTM zone letter. Used only when `ego_start_position` is not set.
`use_geo_conversion`	`bool`	`true`	When `false`, bypasses UTM/geo conversion and treats all coordinates as SUMO-local. Set to `false` for synthetic scenarios.
`initial_traffic_count`	`int`	`0`	Number of SUMO traffic vehicles to spawn ahead of the ego at startup
`initial_traffic_spacing`	`double`	`20.0`	Distance in metres between each spawned traffic vehicle

Topics

Topic	Type	Direction	Description
`traffic_participants`	`TrafficParticipantSet`	publish	SUMO vehicles converted to ADORe traffic participants
`vehicle_state/traffic_participant`	`TrafficParticipant`	subscribe	Ego vehicle state injected into SUMO each step

Scenarios

Two example scenarios are provided.

circle50m (`sumo_test.launch.py`)

A synthetic 50 m radius circular track with no real-world georeferencing. Uses local SUMO coordinates directly with use_geo_conversion: false.

SUMO GUI	ADORe / Lichtblick

make cli
cd adore_scenarios/simulation_scenarios
ros2 launch sumo_bridge sumo_test.launch.py

OSM example scenario (`sumo_example.launch.py`)

A georeferenced OpenStreetMap scenario. The ego start and goal are specified as lat/lon coordinates. Initial traffic vehicles are spawned ahead of the ego and follow randomised routes through the network including roundabouts.

SUMO GUI	ADORe / Lichtblick

make cli
cd adore_scenarios/simulation_scenarios
ros2 launch sumo_bridge sumo_example.launch.py

Clock Synchronisation

The bridge synchronises SUMO simulation time to the ROS wall clock. Reference times are captured after the first simulation step completes, ensuring both clocks are anchored at the same point. When use_gui is true, the --start flag is passed to sumo-gui so the simulation begins immediately without requiring the play button.

Coordinate Conventions

Convention	Details
ROS yaw (`yaw_angle`)	Radians, counter-clockwise from east
SUMO heading	Degrees, clockwise from north
SUMO `getPosition`	Returns front bumper; the bridge offsets by half vehicle length to publish and consume centre positions
Geo conversion	`convertGeo(lon, lat, ...)` -- argument order is longitude first

Initial Traffic Spawning

When initial_traffic_count > 0 the bridge spawns SUMO-controlled vehicles ahead of the ego at startup. Spawn positions are walked along the actual lane geometry so vehicles land on the road regardless of curvature. Each vehicle receives a unique randomised route built by walking the routing graph forward from its spawn edge, weighted toward higher speed-limit roads. Routes are deterministic per vehicle ID across runs.