From a240cb55df34265f6acecdc15243d3c0099c1f92 Mon Sep 17 00:00:00 2001
From: Henry Dykhne <ehdykhne@uwaterloo.ca>
Date: Thu, 30 Nov 2023 17:16:23 -0500
Subject: [PATCH] alternative wedge implementation completely reworked (its
still slower and worse but at least its only twice as slow rather than 30
times as slow). pr concerns adressed.
---
experiments/test_notebook.ipynb | 10948 +---------------
.../builders/occlusion_manager_builder.py | 10 +-
...manager.py => shadow_occlusion_manager.py} | 55 +-
.../occlusion/wedge_occlusion_manager.py | 97 +
4 files changed, 344 insertions(+), 10766 deletions(-)
rename nuplan/planning/simulation/occlusion/{complete_shadow_occlusion_manager.py => shadow_occlusion_manager.py} (70%)
create mode 100644 nuplan/planning/simulation/occlusion/wedge_occlusion_manager.py
diff --git a/experiments/test_notebook.ipynb b/experiments/test_notebook.ipynb
index a6f3618..ebe111d 100644
--- a/experiments/test_notebook.ipynb
+++ b/experiments/test_notebook.ipynb
@@ -26,7 +26,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/tmp/ipykernel_8331/4095267831.py:5: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
+ "/tmp/ipykernel_10391/4095267831.py:5: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
" from IPython.core.display import display, HTML\n"
]
}
@@ -476,7 +476,7 @@
" #f'observation.checkpoint_path={ckpt_dir}',\n",
" 'worker=sequential',\n",
" '+occlusion=true',\n",
- " '+occlusion.manager_type=complete_shadow', #options: [range, complete_shadow]\n",
+ " '+occlusion.manager_type=wedge', #options: [range, shadow, wedge]\n",
" \"hydra.searchpath=[pkg://tuplan_garage.planning.script.config.common, pkg://tuplan_garage.planning.script.config.simulation, pkg://nuplan.planning.script.config.common, pkg://nuplan.planning.script.experiments]\",\n",
" *DATASET_PARAMS,\n",
"])"
@@ -511,32 +511,32 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "2023-11-29 23:28:28,178 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:19} Building WorkerPool...\n",
- "2023-11-29 23:28:28,179 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:101} Worker: Sequential\n",
- "2023-11-29 23:28:28,179 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:102} Number of nodes: 1\n",
+ "2023-11-30 22:11:11,533 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:19} Building WorkerPool...\n",
+ "2023-11-30 22:11:11,534 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:101} Worker: Sequential\n",
+ "2023-11-30 22:11:11,535 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:102} Number of nodes: 1\n",
"Number of CPUs per node: 1\n",
"Number of GPUs per node: 0\n",
"Number of threads across all nodes: 1\n",
- "2023-11-29 23:28:28,180 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:27} Building WorkerPool...DONE!\n",
- "2023-11-29 23:28:28,180 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:32} Building experiment folders...\n",
- "2023-11-29 23:28:28,180 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:35} \n",
+ "2023-11-30 22:11:11,535 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:27} Building WorkerPool...DONE!\n",
+ "2023-11-30 22:11:11,535 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:32} Building experiment folders...\n",
+ "2023-11-30 22:11:11,535 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:35} \n",
"\n",
- "\tFolder where all results are stored: /home/ehdykhne/Repos/Datasets/nuplan/exp/exp/simulation/closed_loop_reactive_agents/2023.11.29.23.28.27\n",
+ "\tFolder where all results are stored: /home/ehdykhne/Repos/Datasets/nuplan/exp/exp/simulation/closed_loop_reactive_agents/2023.11.30.22.11.11\n",
"\n",
- "2023-11-29 23:28:28,205 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:70} Building experiment folders...DONE!\n",
- "2023-11-29 23:28:28,205 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:52} Building AbstractCallback...\n",
- "2023-11-29 23:28:28,205 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:68} Building AbstractCallback: 0...DONE!\n",
- "2023-11-29 23:28:28,206 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:49} Building simulations...\n",
- "2023-11-29 23:28:28,206 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:55} Extracting scenarios...\n",
- "2023-11-29 23:28:28,206 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/common/utils/distributed_scenario_filter.py:83} Building Scenarios in mode DistributedMode.SINGLE_NODE\n",
- "2023-11-29 23:28:28,206 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:18} Building AbstractScenarioBuilder...\n",
- "2023-11-29 23:28:28,217 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:21} Building AbstractScenarioBuilder...DONE!\n",
- "2023-11-29 23:28:28,217 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:35} Building ScenarioFilter...\n",
- "2023-11-29 23:28:28,218 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:44} Building ScenarioFilter...DONE!\n",
- "2023-11-29 23:28:28,405 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:76} Building metric engines...\n",
- "2023-11-29 23:28:28,428 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:78} Building metric engines...DONE\n",
- "2023-11-29 23:28:28,428 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:82} Building simulations from 1 scenarios...\n",
- "2023-11-29 23:28:28,844 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:142} Building simulations...DONE!\n"
+ "2023-11-30 22:11:11,557 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:70} Building experiment folders...DONE!\n",
+ "2023-11-30 22:11:11,557 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:52} Building AbstractCallback...\n",
+ "2023-11-30 22:11:11,557 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:68} Building AbstractCallback: 0...DONE!\n",
+ "2023-11-30 22:11:11,557 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:49} Building simulations...\n",
+ "2023-11-30 22:11:11,557 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:55} Extracting scenarios...\n",
+ "2023-11-30 22:11:11,558 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/common/utils/distributed_scenario_filter.py:83} Building Scenarios in mode DistributedMode.SINGLE_NODE\n",
+ "2023-11-30 22:11:11,558 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:18} Building AbstractScenarioBuilder...\n",
+ "2023-11-30 22:11:11,569 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:21} Building AbstractScenarioBuilder...DONE!\n",
+ "2023-11-30 22:11:11,569 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:35} Building ScenarioFilter...\n",
+ "2023-11-30 22:11:11,570 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:44} Building ScenarioFilter...DONE!\n",
+ "2023-11-30 22:11:11,757 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:76} Building metric engines...\n",
+ "2023-11-30 22:11:11,780 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:78} Building metric engines...DONE\n",
+ "2023-11-30 22:11:11,781 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:82} Building simulations from 1 scenarios...\n",
+ "2023-11-30 22:11:12,199 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:142} Building simulations...DONE!\n"
]
}
],
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- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn[8], line 11\u001b[0m\n\u001b[1;32m 8\u001b[0m runner\u001b[38;5;241m.\u001b[39msimulation\u001b[38;5;241m.\u001b[39mcallback\u001b[38;5;241m.\u001b[39mon_step_start(runner\u001b[38;5;241m.\u001b[39msimulation\u001b[38;5;241m.\u001b[39msetup, runner\u001b[38;5;241m.\u001b[39mplanner)\n\u001b[1;32m 10\u001b[0m \u001b[38;5;66;03m# Perform step\u001b[39;00m\n\u001b[0;32m---> 11\u001b[0m planner_input \u001b[38;5;241m=\u001b[39m \u001b[43mrunner\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_simulation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_planner_input\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;66;03m# Execute specific callback\u001b[39;00m\n\u001b[1;32m 14\u001b[0m runner\u001b[38;5;241m.\u001b[39m_simulation\u001b[38;5;241m.\u001b[39mcallback\u001b[38;5;241m.\u001b[39mon_planner_start(runner\u001b[38;5;241m.\u001b[39msimulation\u001b[38;5;241m.\u001b[39msetup, runner\u001b[38;5;241m.\u001b[39mplanner)\n",
- "File \u001b[0;32m~/Repos/nuplan-devkit/nuplan/planning/simulation/simulation.py:143\u001b[0m, in \u001b[0;36mSimulation.get_planner_input\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 141\u001b[0m history_input \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_history_buffer\n\u001b[1;32m 142\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_occlusion_manager \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 143\u001b[0m history_input \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_occlusion_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mocclude_input\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhistory_input\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 145\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExecuting \u001b[39m\u001b[38;5;132;01m{\u001b[39;00miteration\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 146\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m PlannerInput(iteration\u001b[38;5;241m=\u001b[39miteration, history\u001b[38;5;241m=\u001b[39mhistory_input, traffic_light_data\u001b[38;5;241m=\u001b[39mtraffic_light_data)\n",
- "File \u001b[0;32m~/Repos/nuplan-devkit/nuplan/planning/simulation/occlusion/abstract_occlusion_manager.py:45\u001b[0m, in \u001b[0;36mAbstractOcclusionManager.occlude_input\u001b[0;34m(self, input_buffer)\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m ego_state, observations \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(ego_state_buffer, observations_buffer):\n\u001b[1;32m 44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ego_state\u001b[38;5;241m.\u001b[39mtime_us \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_visible_agent_cache:\n\u001b[0;32m---> 45\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_visible_agent_cache[ego_state\u001b[38;5;241m.\u001b[39mtime_us] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_compute_visible_agents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mego_state\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobservations\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 47\u001b[0m output_buffer \u001b[38;5;241m=\u001b[39m SimulationHistoryBuffer(ego_state_buffer, \\\n\u001b[1;32m 48\u001b[0m deque([\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mask_input(ego_state\u001b[38;5;241m.\u001b[39mtime_us, observations) \u001b[38;5;28;01mfor\u001b[39;00m ego_state, observations \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(ego_state_buffer, observations_buffer)]), \\\n\u001b[1;32m 49\u001b[0m sample_interval)\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m output_buffer\n",
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+ "elapsed time: 0.22512388229370117\n",
+ "elapsed time: 0.22021842002868652\n",
+ "elapsed time: 0.22556853294372559\n",
+ "elapsed time: 0.21947193145751953\n",
+ "elapsed time: 0.21569371223449707\n",
+ "elapsed time: 0.20803451538085938\n",
+ "elapsed time: 0.1996312141418457\n",
+ "elapsed time: 0.19556212425231934\n",
+ "elapsed time: 0.19756174087524414\n",
+ "elapsed time: 0.1914689540863037\n",
+ "elapsed time: 0.18631625175476074\n",
+ "elapsed time: 0.1832582950592041\n",
+ "elapsed time: 0.1792597770690918\n",
+ "elapsed time: 0.17596769332885742\n",
+ "elapsed time: 0.1760270595550537\n",
+ "elapsed time: 0.17541003227233887\n",
+ "elapsed time: 0.16789460182189941\n",
+ "elapsed time: 0.164276123046875\n",
+ "elapsed time: 0.16509795188903809\n",
+ "elapsed time: 0.1624126434326172\n",
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+ "elapsed time: 0.154632568359375\n",
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+ "elapsed time: 0.12617826461791992\n",
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+ "elapsed time: 0.07860851287841797\n",
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+ "elapsed time: 0.07809925079345703\n",
+ "elapsed time: 0.07951498031616211\n",
+ "elapsed time: 0.07993435859680176\n",
+ "elapsed time: 0.07770156860351562\n",
+ "elapsed time: 0.0785372257232666\n",
+ "elapsed time: 0.07750558853149414\n",
+ "elapsed time: 0.07692241668701172\n",
+ "elapsed time: 0.07627558708190918\n",
+ "elapsed time: 0.07835149765014648\n",
+ "elapsed time: 0.07673430442810059\n",
+ "elapsed time: 0.0794064998626709\n",
+ "elapsed time: 0.08053350448608398\n",
+ "elapsed time: 0.0787358283996582\n",
+ "elapsed time: 0.07998967170715332\n",
+ "elapsed time: 0.08226990699768066\n",
+ "elapsed time: 0.08355927467346191\n",
+ "elapsed time: 0.08226585388183594\n"
]
}
],
@@ -11303,12 +782,49 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 9,
"id": "e6c22f5f",
"metadata": {
"scrolled": true
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "INFO:bokeh.server.server:Starting Bokeh server version 2.4.3 (running on Tornado 6.2)\n",
+ "WARNING:bokeh.server.util:Host wildcard '*' will allow connections originating from multiple (or possibly all) hostnames or IPs. Use non-wildcard values to restrict access explicitly\n",
+ "INFO:bokeh.server.tornado:User authentication hooks NOT provided (default user enabled)\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.bokehjs_exec.v0+json": "",
+ "text/html": [
+ "<script id=\"1003\">\n",
+ " (function() {\n",
+ " const xhr = new XMLHttpRequest()\n",
+ " xhr.responseType = 'blob';\n",
+ " xhr.open('GET', \"http://localhost:5006/autoload.js?bokeh-autoload-element=1003&bokeh-absolute-url=http://localhost:5006&resources=none\", true);\n",
+ " xhr.onload = function (event) {\n",
+ " const script = document.createElement('script');\n",
+ " const src = URL.createObjectURL(event.target.response);\n",
+ " script.src = src;\n",
+ " document.body.appendChild(script);\n",
+ " };\n",
+ " xhr.send();\n",
+ " })();\n",
+ "</script>"
+ ]
+ },
+ "metadata": {
+ "application/vnd.bokehjs_exec.v0+json": {
+ "server_id": "d1835ed663314ae5a49980c801f29d2d"
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
"source": [
"from tutorials.utils.tutorial_utils import visualize_history\n",
"visualize_history(runner.simulation._history, runner.scenario, bokeh_port=5006)"
diff --git a/nuplan/planning/script/builders/occlusion_manager_builder.py b/nuplan/planning/script/builders/occlusion_manager_builder.py
index 2a1b2ae..3a95c9c 100644
--- a/nuplan/planning/script/builders/occlusion_manager_builder.py
+++ b/nuplan/planning/script/builders/occlusion_manager_builder.py
@@ -4,7 +4,9 @@ from omegaconf import DictConfig
from nuplan.planning.scenario_builder.abstract_scenario import AbstractScenario
from nuplan.planning.simulation.occlusion.abstract_occlusion_manager import AbstractOcclusionManager
from nuplan.planning.simulation.occlusion.range_occlusion_manager import RangeOcclusionManager
-from nuplan.planning.simulation.occlusion.complete_shadow_occlusion_manager import CompleteShadowOcclusionManager
+from nuplan.planning.simulation.occlusion.shadow_occlusion_manager import ShadowOcclusionManager
+from nuplan.planning.simulation.occlusion.wedge_occlusion_manager import WedgeOcclusionManager
+
def build_occlusion_manager(occlusion_cfg: DictConfig, scenario: AbstractScenario) -> AbstractOcclusionManager:
@@ -17,8 +19,10 @@ def build_occlusion_manager(occlusion_cfg: DictConfig, scenario: AbstractScenari
occlusion_manager: AbstractOcclusionManager
if occlusion_cfg.manager_type == 'range': #masks everyone further away than a set threshold
occlusion_manager = RangeOcclusionManager(scenario)
- elif occlusion_cfg.manager_type == 'complete_shadow': #masks everyone who is is completely occluded
- occlusion_manager = CompleteShadowOcclusionManager(scenario)
+ elif occlusion_cfg.manager_type == 'shadow': #masks everyone who is is occluded by shadows
+ occlusion_manager = ShadowOcclusionManager(scenario)
+ elif occlusion_cfg.manager_type == 'wedge': #calculates occlusions via wedges
+ occlusion_manager = WedgeOcclusionManager(scenario)
else:
raise ValueError(f"Invalid manager_type selected. Got {occlusion_cfg.manager_type}")
diff --git a/nuplan/planning/simulation/occlusion/complete_shadow_occlusion_manager.py b/nuplan/planning/simulation/occlusion/shadow_occlusion_manager.py
similarity index 70%
rename from nuplan/planning/simulation/occlusion/complete_shadow_occlusion_manager.py
rename to nuplan/planning/simulation/occlusion/shadow_occlusion_manager.py
index 2c2ab1d..72adf41 100644
--- a/nuplan/planning/simulation/occlusion/complete_shadow_occlusion_manager.py
+++ b/nuplan/planning/simulation/occlusion/shadow_occlusion_manager.py
@@ -14,24 +14,24 @@ import numpy as np
import time
-class CompleteShadowOcclusionManager(AbstractOcclusionManager):
+class ShadowOcclusionManager(AbstractOcclusionManager):
"""
Range occlusion manager. Occludes all objects outside of a given
range of the ego.
"""
+ ORIG = (0,0)
+
def __init__(
self,
scenario: AbstractScenario,
horizon_threshold: float = 1000, # meters since that is how far a standing human can see unblocked before the curvature of the earth cuts your line of sight
min_rad: float = 0.035, # minimum radians that the vehicle must take up to be observed (0.035 = aprox 2 degrees)
- num_wedges: float = 180 # gives wedge width of roughly 2 degrees
-
):
super().__init__(scenario)
self.horizon_threshold = horizon_threshold
self.min_rad = min_rad
- self.num_wedges = num_wedges
+
def _compute_visible_agents(self, ego_state: EgoState, observations: DetectionsTracks) -> set:
"""
Returns set of track tokens that represents the observations visible to the ego
@@ -41,7 +41,7 @@ class CompleteShadowOcclusionManager(AbstractOcclusionManager):
return self._determine_occlusions(ego_state.agent, observations.tracked_objects.tracked_objects)
def _determine_occlusions(self, observer: AgentState, targets:List[AgentState]) -> set:
- start = time.time()
+ # start = time.time()
not_occluded = set() # Visible track token set
shadow_polys = deque([])
@@ -65,7 +65,7 @@ class CompleteShadowOcclusionManager(AbstractOcclusionManager):
combined_shadow_poly = unary_union(shadow_polys)
- observer_origin = Point((0,0))
+ observer_origin = Point(ORIG)
for target in targets: #now we check if each target is contained within the shadows
corners_list = target.box.all_corners() #Return 4 corners of oriented box (FL, RL, RR, FR) Point2D
corners = []
@@ -77,11 +77,11 @@ class CompleteShadowOcclusionManager(AbstractOcclusionManager):
hull = unary_union([diff_poly, observer_origin]).convex_hull
if isinstance(hull, Polygon):
- neighbor_1, neighbor_2 = self._get_two_neighbors((0,0), hull)
+ neighbor_1, neighbor_2 = self._get_two_neighbors(ORIG, hull)
radians = abs(math.atan2(neighbor_1.x*neighbor_2.y - neighbor_1.y*neighbor_2.x, neighbor_1.x*neighbor_2.x + neighbor_1.y*neighbor_2.y ))
if radians > self.min_rad:
not_occluded.add(target.metadata.track_token)
- print('elapsed time:', time.time() - start)
+ # print('elapsed time:', time.time() - start)
return not_occluded
def _get_two_neighbors(self, point, polygon) -> List[Point]:
@@ -100,42 +100,3 @@ class CompleteShadowOcclusionManager(AbstractOcclusionManager):
two_neighbors[0] = Point(two_neighbors[0])
two_neighbors[1] = Point(two_neighbors[1])
return two_neighbors
-
- #alternative occlusion implementation. measured to be an order of magnitude slower
- def _determine_occlusions_alt(self, observer: AgentState, targets:List[AgentState]) -> set:
- start = time.time()
- not_occluded = set() # Visible track token set
- rads = np.linspace(0,2*math.pi,self.num_wedges+1)
-
- for i in range(len(rads)-1):
- build_wedge = time.time()
-
- d1 = rads[i]#create wedge
- d2 = rads[i+1]
- p1 = (self.horizon_threshold * math.cos(d1), self.horizon_threshold * math.sin(d1))
- p2 = (self.horizon_threshold * math.cos(d2), self.horizon_threshold * math.sin(d2))
- wedge = Polygon([(0,0), p1, p2])
- print('build_wedge', time.time() - build_wedge)
-
-
- wedge_occupiers = []
- target_looping = time.time()
-
- collect_targets = time.time()
- for target in targets:
- corners_list = target.box.all_corners() #Return 4 corners of oriented box (FL, RL, RR, FR) Point2D
- corners = []
- for corner in corners_list:
- corners.append((corner.x - observer.center.x, corner.y - observer.center.y)) #we shift the corners and move them to a different data structure we can play with
- target_poly = Polygon(corners)
- if wedge.intersects(target_poly):
- wedge_occupiers.append(target)
- print('collect_targets', time.time() - collect_targets)
-
- sort_time = time.time()
- if len(wedge_occupiers) > 0:
- wedge_occupiers.sort(key=lambda x: (x.center.x - observer.center.x)**2 + (x.center.y - observer.center.y)**2)
- not_occluded.add(wedge_occupiers[0].metadata.track_token)
- print('sort_time', time.time() - sort_time)
- print('elapsed time:', time.time() - start)
- return not_occluded
\ No newline at end of file
diff --git a/nuplan/planning/simulation/occlusion/wedge_occlusion_manager.py b/nuplan/planning/simulation/occlusion/wedge_occlusion_manager.py
new file mode 100644
index 0000000..3ead939
--- /dev/null
+++ b/nuplan/planning/simulation/occlusion/wedge_occlusion_manager.py
@@ -0,0 +1,97 @@
+from nuplan.common.actor_state.ego_state import EgoState
+from nuplan.planning.scenario_builder.abstract_scenario import AbstractScenario
+from nuplan.planning.simulation.observation.observation_type import DetectionsTracks
+from nuplan.planning.simulation.occlusion.abstract_occlusion_manager import AbstractOcclusionManager
+from nuplan.common.actor_state.agent_state import AgentState
+from nuplan.common.actor_state.tracked_objects_types import AGENT_TYPES, STATIC_OBJECT_TYPES, TrackedObjectType
+from shapely.geometry import Polygon, Point, MultiPoint
+from shapely.ops import unary_union
+from typing import List
+from collections import deque
+import math
+import numpy as np
+
+import time
+
+
+class WedgeOcclusionManager(AbstractOcclusionManager):
+ """
+ Range occlusion manager. Occludes all objects outside of a given
+ range of the ego.
+ """
+
+ ORIG = (0,0)
+
+ def __init__(
+ self,
+ scenario: AbstractScenario,
+ horizon_threshold: float = 1000, # meters since that is how far a standing human can see unblocked before the curvature of the earth cuts your line of sight
+ num_wedges: float = 180 # gives wedge width of roughly 2 degrees
+
+ ):
+ super().__init__(scenario)
+ self.horizon_threshold = horizon_threshold
+ self.num_wedges = num_wedges
+
+ def _compute_visible_agents(self, ego_state: EgoState, observations: DetectionsTracks) -> set:
+ """
+ Returns set of track tokens that represents the observations visible to the ego
+ at this time step.
+ """
+ # Visible track token set
+ return self._determine_occlusions(ego_state.agent, observations.tracked_objects.tracked_objects)
+
+ # wedge based occlusion implementation. about half as fast and the occlusions flicker more but it should scale better if you have tons of occluders
+ def _determine_occlusions(self, observer: AgentState, targets:List[AgentState]) -> set:
+ start = time.time()
+ rads = np.linspace(0,2*math.pi,self.num_wedges+1)
+ wedges = set()
+
+ for i in range(len(rads)-1):
+ d1 = rads[i] # create wedge
+ d2 = rads[i+1]
+ p1 = (self.horizon_threshold * math.cos(d1), self.horizon_threshold * math.sin(d1))
+ p2 = (self.horizon_threshold * math.cos(d2), self.horizon_threshold * math.sin(d2))
+ wedge = Polygon([ORIG, p1, p2])
+
+ wedges.add(wedge)
+
+ sorted_targets = sorted(targets, key=lambda x: (x.center.x - observer.center.x)**2 + (x.center.y - observer.center.y)**2) #sorts closest to farthest
+
+ not_occluded = set() # Visible track token set
+
+ for target in sorted_targets:
+ corners_list = target.box.all_corners() #Return 4 corners of oriented box (FL, RL, RR, FR) Point2D
+ corners = []
+ for corner in corners_list:
+ corners.append((corner.x - observer.center.x, corner.y - observer.center.y)) #we shift the corners and move them to a different data structure we can play with
+ target_poly = Polygon(corners)
+
+ to_remove = set()
+ for wedge in wedges:
+ if wedge.intersects(target_poly):
+ if target.tracked_object_type == TrackedObjectType.VEHICLE or target.tracked_object_type == TrackedObjectType.EGO:
+ to_remove.add(wedge)
+ not_occluded.add(target.metadata.track_token)
+ wedges -= to_remove
+
+
+ print('elapsed time:', time.time() - start)
+ return not_occluded
+
+ def _get_two_neighbors(self, point, polygon) -> List[Point]:
+ """retrieve the two neighboring points of point in the polygon
+ :point: a tuple representing a point of the polygon
+ :polygon: a shapely Polygon
+ return: a tuple of the two points immediately neighbors of point
+ """
+ points = list(polygon.exterior.coords)
+ ndx = points.index(point)
+ two_neighbors = [points[(ndx-1)%len(points)], points[(ndx+1)%len(points)]]
+ if two_neighbors[0] == point:
+ two_neighbors[0] = points[(ndx-2)%len(points)]
+ if two_neighbors[1] == point:
+ two_neighbors[1] = points[(ndx+2)%len(points)]
+ two_neighbors[0] = Point(two_neighbors[0])
+ two_neighbors[1] = Point(two_neighbors[1])
+ return two_neighbors
--
GitLab