Add CARLA's traffic lights, stop signs and stop lines to Town10HD_Opt

README.md

@@ -46,7 +46,7 @@ CARLA's [Town 10](https://carla-ue5.readthedocs.io/en/latest/map_town10/): an in
 | `lanelet2_map.osm` | `pointcloud_map.pcd` |
 | --- | --- |
 | [![The Town10HD_Opt lanelet2 map](preview/Town10HD_Opt.svg)](https://hakuturu583.github.io/simple_lanelet2/embed.html?map=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FAutowareFoundation%2Fcarla-ue5-maps%2Fresolve%2Fmain%2Fautoware_maps%2FTown10HD_Opt%2Flanelet2_map.osm&theme=dark) | ![The Town10HD_Opt point cloud map](preview/Town10HD_Opt.pointcloud.png) |
-| 168 lanelets, 279 linestrings, 9,214 points. Drawn by [simple_lanelet2](https://github.com/hakuturu583/simple_lanelet2), which also renders it in the browser — **click it to open the file in this dataset in that viewer**. | 1,851,689 points over 368 x 357 x 31 m, voxel-downsampled at 0.2 m. Seen from above, coloured by height — the road surface is the dark ground, and what stands beside it is the buildings, the street trees along the boulevards and the roundabout at the top right. |
+| 168 lanelets, 487 linestrings, 9,650 points, and 33 regulatory elements (15 signals and 3 stop signs). Drawn by [simple_lanelet2](https://github.com/hakuturu583/simple_lanelet2), which also renders it in the browser — **click it to open the file in this dataset in that viewer**. | 1,851,689 points over 368 x 357 x 31 m, voxel-downsampled at 0.2 m. Seen from above, coloured by height — the road surface is the dark ground, and what stands beside it is the buildings, the street trees along the boulevards and the roundabout at the top right. |
 
 The two are the same town in the two forms Autoware reads it in, drawn to the same frame. What the point cloud shows and the lanelet2 map does not is the reason the point cloud is here at all: this is Unreal Engine 5 geometry, not the 0.9 geometry the published map was recorded on.
 
@@ -112,19 +112,34 @@ Autoware and CARLA share an origin here, so `map_origin_x` and `map_origin_y` st
 
 </details>
 
+<details>
+<summary>Traffic lights and stop lines</summary>
+
+The published lanelet2 map has no regulatory elements, so nothing in it says where a vehicle stops or which signal it obeys: Autoware cannot look for the signals, and a scenario cannot ask for "the approach to a signalised junction".
+
+The map here carries CARLA's own: every signal and stop sign of the 0.10 town, read from a running server by [`add_regulatory_elements.py`](https://gist.github.com/hakuturu583/f11582b8ca65a5e2efae9fe884e1dfc0), a one-off script kept as a gist rather than in this dataset. For each lane a signal or stop sign governs, CARLA's stop waypoints (or the sign's trigger volume) are followed to where the lane enters its junction, and there:
+
+- the stop line is the end edge of the approach lanelet, through its two existing nodes -- the nodes every junction lanelet leaving it starts from;
+- a `traffic_light` regulatory element (a `traffic_sign` one for a stop sign) has that stop line as its `ref_line`, and every junction lanelet (`turn_direction`) leaving the approach references it;
+- each signal head is a `traffic_light` linestring along the bottom of its housing, left to right as the driver sees it, with its `height`, and `light_bulbs` red, yellow and green from the top; a stop sign is a `traffic_sign` linestring of subtype `stop_sign`.
+
+That is 30 traffic-light regulatory elements for CARLA's 15 signals, one per lane they govern, and 3 for its stop signs, on 62 junction lanelets. Its two yield signs have no stop line and are not written.
+
+</details>
+
 <details>
 <summary>Lane changes need tagged lane boundaries</summary>
 
 The published lanelet2 maps carry geometry only: their boundary ways have no `type`. Lanelet2's traffic rules read the shared boundary to decide whether a vehicle may cross it, and an untagged boundary is one it may not. The routing graph then holds `adjacentLeft` / `adjacentRight` relations but no `left` / `right` ones, Autoware's route handler finds no lane change target, and the ego drives to the end of its own lane whatever the route says.
 
-The map here is the published one, untouched, so it has this property. Tagging the dividers between same-direction lanes as `line_thin` / `dashed` is what makes crossing legal. Tag only the lanes a scenario drives: these towns are built from thousands of very short lanelets, and with lane changes legal everywhere the behavior planner has been seen to spin without ever publishing a path.
+The map here keeps the published geometry, so it has this property. Tagging the dividers between same-direction lanes as `line_thin` / `dashed` is what makes crossing legal. Tag only the lanes a scenario drives: these towns are built from thousands of very short lanelets, and with lane changes legal everywhere the behavior planner has been seen to spin without ever publishing a path.
 
 </details>
 
 <details>
 <summary>Provenance</summary>
 
-`lanelet2_map.osm` is a verbatim copy of [`maps/vector_maps/lanelet2/Town10HD.osm`](https://bitbucket.org/carla-simulator/autoware-contents/src/master/maps/vector_maps/lanelet2/Town10HD.osm) in [carla-simulator/autoware-contents](https://bitbucket.org/carla-simulator/autoware-contents), with SHA-256 `cdd0a28664bcf9b5bd8867584a6fa6a02fa0f75a7c3dbb901ca216128ef86a17`. `map_projector_info.yaml` states the projector that file is drawn against.
+`lanelet2_map.osm` started as a verbatim copy of [`maps/vector_maps/lanelet2/Town10HD.osm`](https://bitbucket.org/carla-simulator/autoware-contents/src/master/maps/vector_maps/lanelet2/Town10HD.osm) in [carla-simulator/autoware-contents](https://bitbucket.org/carla-simulator/autoware-contents), with SHA-256 `cdd0a28664bcf9b5bd8867584a6fa6a02fa0f75a7c3dbb901ca216128ef86a17`. Two things have been added to it, and nothing of the original geometry changed: the `turn_direction` tags of its junction lanelets, read from CARLA's OpenDRIVE, and the traffic lights, stop signs and stop lines above, written by [`add_regulatory_elements.py`](https://gist.github.com/hakuturu583/f11582b8ca65a5e2efae9fe884e1dfc0) from a CARLA 0.10.0 server. `map_projector_info.yaml` states the projector that file is drawn against.
 
 `pointcloud_map.pcd` was recorded from a running CARLA 0.10.0 server. A LiDAR with no vehicle attached is placed at every lane sample of the world, 8 m apart and 2.0 m above the road, with an 80 m range. The returns are accumulated in the Autoware map frame and voxel-downsampled at 0.2 m. The recorder is `docker/devcontainer/carla/build-pointcloud-map.py` in [autowarefoundation/autoware](https://github.com/autowarefoundation/autoware).
 

autoware_maps/Town10HD_Opt/lanelet2_map.osm

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