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Comma Device
2026-01-11 18:23:29 +08:00
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tools/car_porting/examples/find_segments_with_message.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 85,
"id": "facb8edc-9924-491a-a4dd-fe6135b0c6c4",
"metadata": {},
"outputs": [],
"source": [
"# Import all cars from opendbc\n",
"\n",
"from opendbc.car import structs\n",
"from opendbc.car.values import PLATFORMS as TEST_PLATFORMS\n",
"\n",
"# Example: add additional platforms/segments to test outside of commaCarSegments\n",
"\n",
"EXTRA_SEGMENTS = {\n",
" # \"81dd9e9fe256c397/0000001f--97c42cf98d\", # Volkswagen ID.4 test route, new car port, not in public dataset\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "ed1c8aec-c274-4c61-b83d-711ea194bf86",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Searching 221 platforms\n",
"No segments available for DODGE_DURANGO\n",
"No segments available for FORD_RANGER_MK2\n",
"No segments available for HOLDEN_ASTRA\n",
"No segments available for CADILLAC_ATS\n",
"No segments available for CHEVROLET_MALIBU\n",
"No segments available for CADILLAC_XT4\n",
"No segments available for CHEVROLET_VOLT_2019\n",
"No segments available for CHEVROLET_TRAVERSE\n",
"No segments available for GMC_YUKON\n",
"No segments available for HONDA_ODYSSEY_CHN\n",
"No segments available for HYUNDAI_KONA_2022\n",
"No segments available for HYUNDAI_NEXO_1ST_GEN\n",
"No segments available for GENESIS_GV70_ELECTRIFIED_1ST_GEN\n",
"No segments available for GENESIS_G80_2ND_GEN_FL\n",
"No segments available for RIVIAN_R1_GEN1\n",
"No segments available for SUBARU_FORESTER_HYBRID\n",
"No segments available for TESLA_MODEL_3\n",
"No segments available for TESLA_MODEL_Y\n",
"No segments available for TOYOTA_RAV4_PRIME\n",
"No segments available for TOYOTA_SIENNA_4TH_GEN\n",
"No segments available for LEXUS_LC_TSS2\n",
"No segments available for VOLKSWAGEN_CADDY_MK3\n",
"No segments available for VOLKSWAGEN_CRAFTER_MK2\n",
"No segments available for VOLKSWAGEN_JETTA_MK6\n",
"Searching 577 segments\n"
]
}
],
"source": [
"import random\n",
"\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"from openpilot.tools.lib.comma_car_segments import get_comma_car_segments_database\n",
"\n",
"\n",
"MAX_SEGS_PER_PLATFORM = 3 # Increase this to search more segments\n",
"\n",
"database = get_comma_car_segments_database()\n",
"TEST_SEGMENTS = []\n",
"\n",
"print(f\"Searching {len(TEST_PLATFORMS)} platforms\")\n",
"\n",
"for platform in TEST_PLATFORMS:\n",
" if platform not in database:\n",
" print(f\"No segments available for {platform}\")\n",
" continue\n",
" \n",
" all_segments = database[platform]\n",
" NUM_SEGMENTS = min(len(all_segments), MAX_SEGS_PER_PLATFORM)\n",
" TEST_SEGMENTS.extend(random.sample(all_segments, NUM_SEGMENTS))\n",
"\n",
"TEST_SEGMENTS.extend(EXTRA_SEGMENTS)\n",
"\n",
"print(f\"Searching {len(TEST_SEGMENTS)} segments\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0c75e8f2-4f5f-4f89-b8db-5223a6534a9f",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "27a243c33de44498b2b946190df44b23",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"segments searched: 0%| | 0/577 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Match found: 0f53b336851e1384/2023-11-20--09-44-03/12/s CHRYSLER PACIFICA HYBRID 2018 ['VW CAN Ign']\n",
"Match found: 7620ad20d3cefc64/2023-10-28--08-14-40/3/s CHRYSLER PACIFICA HYBRID 2018 ['VW CAN Ign']\n",
"Match found: 00d247a9bb1f9196/2023-11-06--13-33-17/9/s CHRYSLER PACIFICA HYBRID 2018 ['VW CAN Ign']\n",
"Match found: 120a432f63cb0de2/2023-10-30--20-01-34/1/s CHRYSLER PACIFICA HYBRID 2019 ['VW CAN Ign']\n",
"Match found: b70b56b76a6217f2/2023-12-19--08-30-22/35/s CHRYSLER PACIFICA HYBRID 2019 ['VW CAN Ign']\n",
"Match found: 97e388680a6716ed/2024-01-17--10-15-13/9/s CHRYSLER PACIFICA HYBRID 2019 ['VW CAN Ign']\n",
"Match found: 2137b01aa0ca63f9/2024-01-06--22-06-14/70/s CHRYSLER PACIFICA 2018 ['VW CAN Ign']\n",
"Match found: 8fc6a1b72c8b1357/2023-11-06--07-50-05/8/s CHRYSLER PACIFICA 2018 ['VW CAN Ign']\n",
"Match found: 7e705eb5c27a49cc/2024-01-18--16-51-20/3/s CHRYSLER PACIFICA 2018 ['VW CAN Ign']\n",
"Match found: 12208e5acdc97eb3/2024-01-20--14-46-24/12/s CHRYSLER PACIFICA 2020 ['VW CAN Ign']\n",
"Match found: 12208e5acdc97eb3/2023-11-30--12-01-09/2/s CHRYSLER PACIFICA 2020 ['VW CAN Ign']\n",
"Match found: 9cad19e0efce3650/2024-01-26--10-24-52/27/s CHRYSLER PACIFICA 2020 ['VW CAN Ign']\n",
"Match found: 9db428338427dec2/2023-11-05--18-40-09/21/s JEEP GRAND CHEROKEE V6 2018 ['VW CAN Ign']\n",
"Match found: d50ada8ee55a5e74/2023-12-11--13-38-09/0/s JEEP GRAND CHEROKEE V6 2018 ['VW CAN Ign']\n",
"Match found: 900dfa83b4addfe6/2023-12-30--19-20-08/28/s JEEP GRAND CHEROKEE V6 2018 ['VW CAN Ign']\n",
"Match found: 20acda0eb23d7f23/2024-01-19--17-33-26/41/s JEEP GRAND CHEROKEE 2019 ['VW CAN Ign']\n",
"Match found: 1cc3b46843cad2ca/2024-01-10--20-20-54/24/s JEEP GRAND CHEROKEE 2019 ['VW CAN Ign']\n",
"Match found: 2d9b6425552c52c1/2023-12-07--10-31-46/22/s JEEP GRAND CHEROKEE 2019 ['VW CAN Ign']\n",
"Match found: ae679616266f4096/2023-12-04--13-13-56/16/s RAM HD 5TH GEN ['Tesla 3/Y CAN Ign']\n",
"Match found: ae679616266f4096/2024-01-08--07-58-12/65/s RAM HD 5TH GEN ['Tesla 3/Y CAN Ign']\n",
"Match found: ae679616266f4096/2023-12-05--15-43-46/25/s RAM HD 5TH GEN ['Tesla 3/Y CAN Ign']\n",
"Match found: 6dae2984cc53cd7f/2024-01-09--21-41-11/4/s FORD BRONCO SPORT 1ST GEN ['Rivian CAN Ign']\n",
"Match found: 440a155809ba2b6d/2023-12-30--08-51-53/2/s FORD BRONCO SPORT 1ST GEN ['Rivian CAN Ign']\n",
"Match found: 6dae2984cc53cd7f/2024-01-06--10-11-07/1/s FORD BRONCO SPORT 1ST GEN ['Rivian CAN Ign']\n",
"Match found: a4218e6416dfd978/2023-11-27--13-48-46/19/s FORD ESCAPE 4TH GEN ['Rivian CAN Ign']\n",
"Match found: a4218e6416dfd978/2023-11-10--14-13-14/0/s FORD ESCAPE 4TH GEN ['Rivian CAN Ign']\n",
"Match found: a4218e6416dfd978/2023-11-27--13-48-46/4/s FORD ESCAPE 4TH GEN ['Rivian CAN Ign']\n",
"Match found: 8a732841c3a8d5ef/2023-12-10--19-02-33/3/s FORD EXPLORER 6TH GEN ['Rivian CAN Ign']\n",
"Match found: 0b91b433b9332780/2023-12-28--14-02-49/4/s FORD EXPLORER 6TH GEN ['Rivian CAN Ign']\n",
"Match found: 8a732841c3a8d5ef/2023-11-09--07-28-12/1/s FORD EXPLORER 6TH GEN ['Rivian CAN Ign']\n",
"Match found: e886087f430e7fe7/2023-11-05--19-59-40/59/s FORD FOCUS 4TH GEN ['Rivian CAN Ign']\n",
"Match found: e886087f430e7fe7/2023-11-05--19-59-40/82/s FORD FOCUS 4TH GEN ['Rivian CAN Ign']\n",
"Match found: e886087f430e7fe7/2023-11-05--19-59-40/106/s FORD FOCUS 4TH GEN ['Rivian CAN Ign']\n"
]
}
],
"source": [
"from openpilot.tools.lib.logreader import LogReader\n",
"from tqdm.notebook import tqdm, tnrange\n",
"\n",
"# Example search for CAN ignition messages\n",
"# Be careful when filtering by bus, account for odd harness arrangements on Honda/HKG\n",
"\n",
"BUSES_TO_SEARCH = [0, 1, 2]\n",
"\n",
"# Support for external Red Panda\n",
"EXTERNAL_PANDA_BUSES = [bus + 4 for bus in BUSES_TO_SEARCH]\n",
"\n",
"MESSAGES_TO_FIND = {\n",
" 0x1F1: \"GM CAN Ign\",\n",
" 0x152: \"Rivian CAN Ign\",\n",
" 0x221: \"Tesla 3/Y CAN Ign\",\n",
" 0x9E: \"Mazda CAN Ign\",\n",
" 0x3C0: \"VW CAN Ign\",\n",
"}\n",
"\n",
"progress_bar = tnrange(len(TEST_SEGMENTS), desc=\"segments searched\")\n",
"\n",
"for segment in TEST_SEGMENTS:\n",
" lr = LogReader(segment)\n",
" CP = lr.first(\"carParams\")\n",
" if CP is None:\n",
" progress_bar.update()\n",
" continue\n",
"\n",
" can_packets = [msg for msg in lr if msg.which() == \"can\"]\n",
" matched_messages = set()\n",
"\n",
" for packet in can_packets:\n",
" for msg in packet.can:\n",
" if msg.address in MESSAGES_TO_FIND and msg.src in (BUSES_TO_SEARCH + EXTERNAL_PANDA_BUSES):\n",
" # print(msg)\n",
" matched_messages.add(msg.address)\n",
"\n",
" if len(matched_messages) > 0:\n",
" message_names = [MESSAGES_TO_FIND[message] for message in matched_messages]\n",
" print(f\"Match found: {segment:<45} {CP.carFingerprint:<38} {message_names}\")\n",
"\n",
" progress_bar.update()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7724dd97-f62e-4fd3-9f64-63d49be669d2",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "9f393e00-8efd-40fb-a41e-d312531a83e8",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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tools/car_porting/examples/ford_vin_fingerprint.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"jupyter": {
"is_executing": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Got 9 Ford cars from opendbc\n"
]
}
],
"source": [
"\"\"\"In this example, we use the public comma car segments database to check if vin fingerprinting is feasible for ford.\"\"\"\n",
"\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"from openpilot.tools.lib.comma_car_segments import get_comma_car_segments_database\n",
"from opendbc.car.ford.values import CAR\n",
"\n",
"database = get_comma_car_segments_database()\n",
"\n",
"platforms = [c.value for c in CAR]\n",
"print(f\"Got {len(platforms)} Ford cars from opendbc\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Adapted from https://github.com/commaai/openpilot/issues/31052#issuecomment-1902690083\n",
"\n",
"MODEL_YEAR_CODES = {'M': 2021, 'N': 2022, 'P': 2023, 'R': 2024, 'S': 2025}\n",
"\n",
"\n",
"F150_CODES = ['F1C', 'F1E', 'W1C', 'W1E', 'X1C', 'X1E', 'W1R', 'W1P', 'W1S', 'W1T']\n",
"LIGHTNING_CODES = ['L', 'V']\n",
"MACHE_CODES = ['K1R', 'K1S', 'K2S', 'K3R', 'K3S', 'K4S']\n",
"\n",
"FORD_VIN_START = ['1FT', '3FM', '5LM']\n",
"\n",
"def ford_vin_fingerprint(vin): # Check if it's a Ford vehicle and determine the model\n",
" vin_positions_567 = vin[4:7]\n",
"\n",
" if vin.startswith('1FT'):\n",
" if vin_positions_567 in F150_CODES:\n",
" if vin[7] in LIGHTNING_CODES:\n",
" return f\"FORD F-150 LIGHTNING 1ST GEN\"\n",
" else:\n",
" return f\"FORD F-150 14TH GEN\"\n",
" elif vin.startswith('3FM'):\n",
" if vin_positions_567 in MACHE_CODES:\n",
" return f\"FORD MUSTANG MACH-E 1ST GEN\"\n",
" elif vin.startswith('5LM'):\n",
" pass\n",
"\n",
" return \"mock\""
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting segments from commaCarSegments dataset:\n",
"Got 287 segments for platform FORD_BRONCO_SPORT_MK1, sampling 5 segments\n",
"Got 137 segments for platform FORD_ESCAPE_MK4, sampling 5 segments\n",
"Got 1041 segments for platform FORD_EXPLORER_MK6, sampling 5 segments\n",
"Got 5 segments for platform FORD_F_150_MK14, sampling 5 segments\n",
"Got 3 segments for platform FORD_F_150_LIGHTNING_MK1, sampling 3 segments\n",
"Got 56 segments for platform FORD_FOCUS_MK4, sampling 5 segments\n",
"Got 637 segments for platform FORD_MAVERICK_MK1, sampling 5 segments\n",
"Got 3 segments for platform FORD_MUSTANG_MACH_E_MK1, sampling 3 segments\n",
"Skipping platform: FORD_RANGER_MK2, no data available\n",
"Segment collection finished\n"
]
}
],
"source": [
"import random\n",
"\n",
"MAX_SEGS_PER_PLATFORM = 5\n",
"\n",
"VINS_TO_CHECK = set()\n",
"\n",
"print(\"Collecting segments from commaCarSegments dataset:\")\n",
"for platform in platforms:\n",
" if platform not in database:\n",
" print(f\"Skipping platform: {platform}, no data available\")\n",
" continue\n",
" \n",
" all_segments = database[platform]\n",
"\n",
" NUM_SEGMENTS = min(len(all_segments), MAX_SEGS_PER_PLATFORM)\n",
"\n",
" print(f\"Got {len(all_segments)} segments for platform {platform}, sampling {NUM_SEGMENTS} segments\")\n",
"\n",
" segments = random.sample(all_segments, NUM_SEGMENTS)\n",
"\n",
" for segment in segments:\n",
" lr = LogReader(segment)\n",
" CP = lr.first(\"carParams\")\n",
" if \"FORD\" not in CP.carFingerprint:\n",
" print(segment, CP.carFingerprint)\n",
" VINS_TO_CHECK.add((CP.carVin, CP.carFingerprint))\n",
"\n",
"print(\"Segment collection finished\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"vin: 3FMCR9B69NRXXXXXX real platform: FORD BRONCO SPORT 1ST GEN determined platform: mock correct: False\n",
"vin: 00000000000XXXXXX real platform: FORD F-150 14TH GEN determined platform: mock correct: False\n",
"vin: 1FMCU9J94MUXXXXXX real platform: FORD ESCAPE 4TH GEN determined platform: mock correct: False\n",
"vin: 3FMTK3SU0MMXXXXXX real platform: FORD MUSTANG MACH-E 1ST GEN determined platform: FORD MUSTANG MACH-E 1ST GEN correct: True\n",
"vin: 1FM5K8HC7MGXXXXXX real platform: FORD EXPLORER 6TH GEN determined platform: mock correct: False\n",
"vin: 5LM5J7XC9LGXXXXXX real platform: FORD EXPLORER 6TH GEN determined platform: mock correct: False\n",
"vin: 1FTVW1EL4NWXXXXXX real platform: FORD F-150 LIGHTNING 1ST GEN determined platform: FORD F-150 LIGHTNING 1ST GEN correct: True\n",
"vin: WF0NXXGCHNJXXXXXX real platform: FORD FOCUS 4TH GEN determined platform: mock correct: False\n",
"vin: 3FTTW8E99NRXXXXXX real platform: FORD MAVERICK 1ST GEN determined platform: mock correct: False\n",
"vin: 1FM5K8GC7LGXXXXXX real platform: FORD EXPLORER 6TH GEN determined platform: mock correct: False\n",
"vin: 3FTTW8E33NRXXXXXX real platform: FORD MAVERICK 1ST GEN determined platform: mock correct: False\n",
"vin: 5LM5J7XC1LGXXXXXX real platform: FORD EXPLORER 6TH GEN determined platform: mock correct: False\n",
"vin: 3FTTW8E3XPRXXXXXX real platform: FORD MAVERICK 1ST GEN determined platform: mock correct: False\n"
]
}
],
"source": [
"for vin, real_fingerprint in VINS_TO_CHECK:\n",
" determined_fingerprint = ford_vin_fingerprint(vin)\n",
" print(f\"vin: {vin} real platform: {real_fingerprint: <30} determined platform: {determined_fingerprint: <30} correct: {real_fingerprint == determined_fingerprint}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
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"version": 3
},
"file_extension": ".py",
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"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

277
tools/car_porting/examples/hkg_canfd_gear_message.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 62,
"id": "228a6736-de31-4255-9d72-a6ff391b968d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 6 qualifying vehicles:\n",
" KIA_EV6\n",
" HYUNDAI_KONA_EV_2ND_GEN\n",
" HYUNDAI_IONIQ_5\n",
" KIA_NIRO_EV_2ND_GEN\n",
" HYUNDAI_IONIQ_6\n",
" GENESIS_GV60_EV_1ST_GEN\n"
]
}
],
"source": [
"from opendbc.car import structs\n",
"from opendbc.car.hyundai.values import CAR, HyundaiFlags\n",
"from opendbc.car.hyundai.fingerprints import FW_VERSIONS\n",
"\n",
"TEST_PLATFORMS = set(CAR.with_flags(HyundaiFlags.CANFD)) & set(CAR.with_flags(HyundaiFlags.EV)) # CAN-FD electric vehicles only\n",
"#TEST_PLATFORMS = set(CAR.with_flags(HyundaiFlags.CANFD)) - set(CAR.with_flags(HyundaiFlags.EV)) # CAN-FD hybrid and ICE vehicles only\n",
"\n",
"print(f\"Found {len(TEST_PLATFORMS)} qualifying vehicles:\")\n",
"for platform in TEST_PLATFORMS:\n",
" print(f\" {platform}\")"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "ed1c8aec-c274-4c61-b83d-711ea194bf86",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting segments from commaCarSegments dataset:\n",
"Got 1300 segments for platform KIA_EV6, sampling 5 segments\n",
"Got 9 segments for platform HYUNDAI_KONA_EV_2ND_GEN, sampling 5 segments\n",
"Got 1570 segments for platform HYUNDAI_IONIQ_5, sampling 5 segments\n",
"Got 34 segments for platform KIA_NIRO_EV_2ND_GEN, sampling 5 segments\n",
"Got 974 segments for platform HYUNDAI_IONIQ_6, sampling 5 segments\n",
"Got 157 segments for platform GENESIS_GV60_EV_1ST_GEN, sampling 5 segments\n",
"Collected 30 segments for analysis\n"
]
}
],
"source": [
"import random\n",
"\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"from openpilot.tools.lib.comma_car_segments import get_comma_car_segments_database\n",
"from opendbc.car.hyundai.values import CAR\n",
"\n",
"database = get_comma_car_segments_database()\n",
"TEST_SEGMENTS = []\n",
"\n",
"MAX_SEGS_PER_PLATFORM = 5 # TODO: Increase this to search more segments\n",
"\n",
"print(\"Collecting segments from commaCarSegments dataset:\")\n",
"for platform in TEST_PLATFORMS:\n",
" assert(platform in database)\n",
" #if platform not in database:\n",
" # print(f\"Skipping platform: {platform}, no data available\")\n",
" # continue\n",
" \n",
" all_segments = database[platform]\n",
"\n",
" NUM_SEGMENTS = min(len(all_segments), MAX_SEGS_PER_PLATFORM)\n",
"\n",
" print(f\"Got {len(all_segments)} segments for platform {platform}, sampling {NUM_SEGMENTS} segments\")\n",
"\n",
" TEST_SEGMENTS.extend(random.sample(all_segments, NUM_SEGMENTS))\n",
"\n",
"print(f\"Collected {len(TEST_SEGMENTS)} segments for analysis\")\n"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "0c75e8f2-4f5f-4f89-b8db-5223a6534a9f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Analyzing segment ff2bd20623fcaeaa/2023-11-26--16-27-04/5/s for KIA EV6 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 3f1a6480f940cf9a/2024-01-10--23-06-11/16/s for KIA EV6 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment b0a9998109ed0053/2023-12-15--11-10-18/12/s for KIA EV6 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 6e14aa2ed85025df/2023-11-15--13-18-12/24/s for KIA EV6 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment a43f21df3a1ca12d/2024-01-25--08-56-22/16/s for KIA EV6 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 1618132d68afc876/2023-12-05--13-49-24/11/s for HYUNDAI KONA ELECTRIC 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 1618132d68afc876/2023-11-26--12-31-18/17/s for HYUNDAI KONA ELECTRIC 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 1618132d68afc876/2023-12-05--11-51-44/3/s for HYUNDAI KONA ELECTRIC 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 1618132d68afc876/2023-08-27--09-32-14/13/s for HYUNDAI KONA 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 1618132d68afc876/2024-01-25--15-07-04/24/s for HYUNDAI KONA ELECTRIC 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 223780ed74116bc2/2023-11-16--09-44-56/15/s for HYUNDAI IONIQ 5 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment ba9951252624f37d/2024-01-20--22-33-23/118/s for HYUNDAI IONIQ 5 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 8379b28e51ceb3b1/2023-11-09--23-21-58/92/s for HYUNDAI IONIQ 5 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 26fac43e27cd6091/2023-11-06--12-23-21/9/s for HYUNDAI IONIQ 5 2022\n",
" GEAR_SHIFTER gear=1.0\n",
" ACCELERATOR gear=0.0\n",
"Analyzing segment 5edb897a0ec7a477/2024-01-13--20-41-36/101/s for HYUNDAI IONIQ 5 2022\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 66cf8ea23b7c2789/2023-12-04--13-48-53/5/s for KIA NIRO EV 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment b153671049a867b3/2023-12-10--20-31-37/2/s for KIA NIRO EV 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment b153671049a867b3/2023-12-03--21-08-30/14/s for KIA NIRO EV 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment b153671049a867b3/2023-11-07--19-52-23/0/s for KIA NIRO EV 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment b153671049a867b3/2023-07-12--19-25-18/6/s for KIA NIRO EV 2ND GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 9ea4578ee2b1abcb/2023-11-18--07-59-26/11/s for HYUNDAI IONIQ 6 2023\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 0ad7facc77922c3e/2023-12-21--17-47-25/18/s for HYUNDAI IONIQ 6 2023\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 26968f888e7330d3/2024-01-02--11-18-37/8/s for HYUNDAI IONIQ 6 2023\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 9ea4578ee2b1abcb/2023-11-27--21-03-24/33/s for HYUNDAI IONIQ 6 2023\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment df7fdd56970d90fe/2024-01-07--01-04-39/26/s for HYUNDAI IONIQ 6 2023\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 94542b2d06f7a9a6/2023-12-11--14-45-44/0/s for GENESIS GV60 ELECTRIC 1ST GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 94542b2d06f7a9a6/2023-12-11--20-57-09/8/s for GENESIS GV60 ELECTRIC 1ST GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 94542b2d06f7a9a6/2024-01-03--12-52-38/5/s for GENESIS GV60 ELECTRIC 1ST GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 94542b2d06f7a9a6/2024-01-19--19-57-52/47/s for GENESIS GV60 ELECTRIC 1ST GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analyzing segment 94542b2d06f7a9a6/2024-01-03--13-01-23/1/s for GENESIS GV60 ELECTRIC 1ST GEN\n",
" GEAR_SHIFTER gear=4.0\n",
" ACCELERATOR gear=5.0\n",
"Analysis finished\n"
]
}
],
"source": [
"import copy\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"from opendbc.can.parser import CANParser\n",
"from opendbc.car.hyundai.values import DBC\n",
"from opendbc.car.hyundai.hyundaicanfd import CanBus\n",
"\n",
"from openpilot.selfdrive.pandad import can_capnp_to_list\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"\n",
"message_names = [\"GEAR_SHIFTER\", \"ACCELERATOR\", \"GEAR\", \"GEAR_ALT\", \"GEAR_ALT_2\"]\n",
"\n",
"for segment in TEST_SEGMENTS:\n",
" lr = LogReader(segment)\n",
" CP = lr.first(\"carParams\")\n",
" if CP is None:\n",
" continue\n",
"\n",
" can_msgs = [msg for msg in lr if msg.which() == \"can\"]\n",
" parser_messages = []\n",
" for name in message_names:\n",
" parser_messages.append((name, 0))\n",
" cp = CANParser(DBC[platform][\"pt\"], parser_messages, CanBus(CP).ECAN)\n",
"\n",
" parsed_message_history = []\n",
" examples = []\n",
"\n",
" for msg in can_msgs:\n",
" cp.update_strings(can_capnp_to_list([msg.as_builder().to_bytes()]))\n",
" parsed_message_history.append(copy.copy(cp.vl))\n",
"\n",
" print(f\"Analyzing segment {segment:<44} for {CP.carFingerprint}\")\n",
" for name in message_names:\n",
" if parsed_message_history[0][name][\"CHECKSUM\"] != 0: # Message is present for this segment\n",
" gear_prev = parsed_message_history[0][name][\"GEAR\"]\n",
" print(f\" {name:<15} gear={gear_prev}\")\n",
" for i, parsed_messages in enumerate(parsed_message_history):\n",
" gear = parsed_messages[name][\"GEAR\"]\n",
" if gear != gear_prev:\n",
" print(f\" *** Signal transition found! ***\")\n",
" examples.append(i)\n",
" gear_prev = gear\n",
"\n",
"print(f\"Analysis finished\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7724dd97-f62e-4fd3-9f64-63d49be669d2",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "9f393e00-8efd-40fb-a41e-d312531a83e8",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

260
tools/car_porting/examples/subaru_fuzzy_fingerprint.ipynb Normal file
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@@ -0,0 +1,260 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"from opendbc.car import structs\n",
"from opendbc.car.subaru.values import CAR, SubaruFlags\n",
"from opendbc.car.subaru.fingerprints import FW_VERSIONS\n",
"\n",
"TEST_PLATFORMS = set(CAR) - CAR.with_flags(SubaruFlags.PREGLOBAL)\n",
"\n",
"Ecu = structs.CarParams.Ecu\n",
"\n",
"FW_BY_ECU = {platform: {ecu: versions for (ecu, addr, sub_addr), versions in fw_versions.items()} for platform, fw_versions in FW_VERSIONS.items()}"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"PLATFORM_CODES = {\n",
" Ecu.abs: {\n",
" 0: {\n",
" b'\\xa5': [CAR.SUBARU_ASCENT, CAR.SUBARU_ASCENT_2023],\n",
" b'\\xa2': [CAR.SUBARU_IMPREZA, CAR.SUBARU_IMPREZA_2020, CAR.SUBARU_CROSSTREK_HYBRID],\n",
" b'\\xa1': [CAR.SUBARU_OUTBACK, CAR.SUBARU_LEGACY, CAR.SUBARU_OUTBACK_2023],\n",
" b'\\xa3': [CAR.SUBARU_FORESTER, CAR.SUBARU_FORESTER_HYBRID, CAR.SUBARU_FORESTER_2022],\n",
" b'z': [CAR.SUBARU_IMPREZA],\n",
" }\n",
" }\n",
"}\n",
"\n",
"YEAR_CODES = {\n",
" Ecu.abs: {\n",
" 2: {\n",
" b'\\x18': 2018,\n",
" b'\\x19': 2019,\n",
" b'\\x20': 2020,\n",
" b'\\x21': 2021,\n",
" b'\\x22': 2022,\n",
" b'\\x23': 2023,\n",
" }\n",
" }\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def get_codes(platforms, codes):\n",
" results = []\n",
" for platform in platforms:\n",
" for ecu in codes:\n",
" for i in codes[ecu]:\n",
" if isinstance(i, tuple):\n",
" j = slice(i[0], i[1])\n",
" else:\n",
" j = slice(i, i+1)\n",
" for version in FW_BY_ECU[platform][ecu]:\n",
" code = version[j]\n",
" if code not in codes[ecu][i]:\n",
" print(f\"{platform} {code.hex()} not in {codes[ecu][i].keys()}\")\n",
" else:\n",
" results.append((platform, codes[ecu][i][code]))\n",
" return results"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SUBARU_IMPREZA 08 not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"SUBARU_IMPREZA 08 not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"SUBARU_IMPREZA 0c not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"SUBARU_IMPREZA 0c not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"SUBARU_IMPREZA 2e not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"SUBARU_IMPREZA 3f not in dict_keys([b'\\x18', b'\\x19', b' ', b'!', b'\"', b'#'])\n",
"correct_year=False platform=SUBARU_FORESTER year=2018 years=[2019, 2020, 2021]\n",
"correct_year=False platform=SUBARU_FORESTER year=2018 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_FORESTER year=2019 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_FORESTER year=2019 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_FORESTER year=2019 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_FORESTER year=2020 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_FORESTER year=2020 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2022 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_OUTBACK year=2022 years=[2020, 2021, 2022]\n",
"correct_year=False platform=SUBARU_FORESTER_HYBRID year=2019 years=[2020]\n",
"correct_year=False platform=SUBARU_CROSSTREK_HYBRID year=2019 years=[2020]\n",
"correct_year=False platform=SUBARU_CROSSTREK_HYBRID year=2021 years=[2020]\n",
"correct_year=True platform=SUBARU_ASCENT_2023 year=2023 years=[2023]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2019 years=[2017, 2018, 2019]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2019 years=[2017, 2018, 2019]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2018 years=[2017, 2018, 2019]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2019 years=[2017, 2018, 2019]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2019 years=[2017, 2018, 2019]\n",
"correct_year=True platform=SUBARU_IMPREZA year=2019 years=[2017, 2018, 2019]\n",
"correct_year=False platform=SUBARU_FORESTER_2022 year=2021 years=[2022, 2023, 2024]\n",
"correct_year=False platform=SUBARU_FORESTER_2022 year=2021 years=[2022, 2023, 2024]\n",
"correct_year=True platform=SUBARU_FORESTER_2022 year=2022 years=[2022, 2023, 2024]\n",
"correct_year=True platform=SUBARU_FORESTER_2022 year=2022 years=[2022, 2023, 2024]\n",
"correct_year=True platform=SUBARU_ASCENT year=2019 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_ASCENT year=2021 years=[2019, 2020, 2021]\n",
"correct_year=True platform=SUBARU_OUTBACK_2023 year=2023 years=[2023]\n",
"correct_year=True platform=SUBARU_OUTBACK_2023 year=2023 years=[2023]\n",
"correct_year=False platform=SUBARU_IMPREZA_2020 year=2019 years=[2020, 2021, 2022]\n",
"correct_year=False platform=SUBARU_IMPREZA_2020 year=2019 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_IMPREZA_2020 year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_IMPREZA_2020 year=2021 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_IMPREZA_2020 year=2021 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_IMPREZA_2020 year=2021 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_IMPREZA_2020 year=2021 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_LEGACY year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_LEGACY year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_LEGACY year=2020 years=[2020, 2021, 2022]\n",
"correct_year=True platform=SUBARU_LEGACY year=2020 years=[2020, 2021, 2022]\n"
]
}
],
"source": [
"def test_year_code(platform, year):\n",
" car_docs = CAR(platform).config.car_docs\n",
" if isinstance(car_docs, list):\n",
" car_docs = car_docs[0]\n",
" years = [int(y) for y in car_docs.year_list]\n",
" correct_year = year in years\n",
" print(f\"{correct_year=!s: <6} {platform=: <32} {year=: <5} {years=}\")\n",
"\n",
"codes = get_codes(TEST_PLATFORMS, YEAR_CODES)\n",
"for platform, year in codes:\n",
" test_year_code(platform, year)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER_HYBRID platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_CROSSTREK_HYBRID platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_CROSSTREK_HYBRID platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_ASCENT_2023 platforms=['SUBARU_ASCENT', 'SUBARU_ASCENT_2023']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER_2022 platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER_2022 platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER_2022 platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_FORESTER_2022 platforms=['SUBARU_FORESTER', 'SUBARU_FORESTER_HYBRID', 'SUBARU_FORESTER_2022']\n",
"in_possible_platforms=True platform=SUBARU_ASCENT platforms=['SUBARU_ASCENT', 'SUBARU_ASCENT_2023']\n",
"in_possible_platforms=True platform=SUBARU_ASCENT platforms=['SUBARU_ASCENT', 'SUBARU_ASCENT_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK_2023 platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_OUTBACK_2023 platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_IMPREZA_2020 platforms=['SUBARU_IMPREZA', 'SUBARU_IMPREZA_2020', 'SUBARU_CROSSTREK_HYBRID']\n",
"in_possible_platforms=True platform=SUBARU_LEGACY platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_LEGACY platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_LEGACY platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n",
"in_possible_platforms=True platform=SUBARU_LEGACY platforms=['SUBARU_OUTBACK', 'SUBARU_LEGACY', 'SUBARU_OUTBACK_2023']\n"
]
}
],
"source": [
"def test_platform_code(platform, platforms):\n",
" platforms = [str(p) for p in platforms]\n",
" in_possible_platforms = platform in platforms\n",
" print(f\"{in_possible_platforms=!s: <6} {platform=: <32} {platforms=}\")\n",
"\n",
"codes = get_codes(TEST_PLATFORMS, PLATFORM_CODES)\n",
"for platform, possible_platforms in codes:\n",
" test_platform_code(platform, possible_platforms)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

128
tools/car_porting/examples/subaru_long_accel.ipynb Normal file
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@@ -0,0 +1,128 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"segments = [\n",
" \"d9df6f87e8feff94|2023-03-28--17-41-10/1:12\"\n",
"]\n",
"platform = \"SUBARU_OUTBACK\"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import copy\n",
"import numpy as np\n",
"\n",
"from opendbc.can.parser import CANParser\n",
"from opendbc.car.subaru.values import DBC\n",
"\n",
"from openpilot.selfdrive.pandad import can_capnp_to_list\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"\n",
"\"\"\"\n",
"In this example, we plot the relationship between Cruise_Brake and Acceleration for stock eyesight.\n",
"\"\"\"\n",
"\n",
"for segment in segments:\n",
" lr = LogReader(segment)\n",
"\n",
" messages = [\n",
" (\"ES_Distance\", 20),\n",
" (\"ES_Brake\", 20),\n",
" (\"ES_Status\", 20),\n",
" ]\n",
"\n",
" cp = CANParser(DBC[platform][\"pt\"], messages, 1)\n",
"\n",
" es_distance_history = []\n",
" es_status_history = []\n",
" es_brake_history = []\n",
" acceleration_history = []\n",
"\n",
" last_acc = 0\n",
"\n",
" for msg in lr:\n",
" if msg.which() == \"can\":\n",
" cp.update_strings(can_capnp_to_list([msg.as_builder().to_bytes()]))\n",
" es_distance_history.append(copy.copy(cp.vl[\"ES_Distance\"]))\n",
" es_brake_history.append(copy.copy(cp.vl[\"ES_Brake\"]))\n",
" es_status_history.append(copy.copy(cp.vl[\"ES_Status\"]))\n",
"\n",
" acceleration_history.append(last_acc)\n",
"\n",
" if msg.which() == \"carState\":\n",
" last_acc = msg.carState.aEgo"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def process(history, func):\n",
" return np.array([func(h) for h in history])\n",
"\n",
"cruise_activated = process(es_status_history, lambda es_status: es_status[\"Cruise_Activated\"])\n",
"cruise_throttle = process(es_distance_history, lambda es_distance: es_distance[\"Cruise_Throttle\"])\n",
"cruise_rpm = process(es_status_history, lambda es_status: es_status[\"Cruise_RPM\"])\n",
"cruise_brake = process(es_brake_history, lambda es_brake: es_brake[\"Brake_Pressure\"])\n",
"acceleration = process(acceleration_history, lambda acc: acc)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"valid_brake = (cruise_activated==1) & (cruise_brake>0) # only when cruise is activated and eyesight is braking\n",
"\n",
"ax = plt.figure().add_subplot()\n",
"\n",
"ax.set_title(\"Brake_Pressure vs Acceleration\")\n",
"ax.set_xlabel(\"Brake_Pessure\")\n",
"ax.set_ylabel(\"Acceleration\")\n",
"ax.scatter(cruise_brake[valid_brake], -acceleration[valid_brake])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

118
tools/car_porting/examples/subaru_steer_temp_fault.ipynb Normal file
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@@ -0,0 +1,118 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# An example of searching through a database of segments for a specific condition, and plotting the results.\n",
"\n",
"segments = [\n",
" \"c3d1ccb52f5f9d65|2023-07-22--01-23-20/6:10\",\n",
"]\n",
"platform = \"SUBARU_OUTBACK\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import copy\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"from opendbc.can.parser import CANParser\n",
"from opendbc.car.subaru.values import CanBus, DBC\n",
"\n",
"from openpilot.selfdrive.pandad import can_capnp_to_list\n",
"from openpilot.tools.lib.logreader import LogReader\n",
"\n",
"\"\"\"\n",
"In this example, we search for positive transitions of Steer_Warning, which indicate that the EPS\n",
"has stopped responding to our messages. This analysis would allow you to find the cause of these\n",
"steer warnings and potentially work around them.\n",
"\"\"\"\n",
"\n",
"for segment in segments:\n",
" lr = LogReader(segment)\n",
"\n",
" can_msgs = [msg for msg in lr if msg.which() == \"can\"]\n",
"\n",
" messages = [\n",
" (\"Steering_Torque\", 50)\n",
" ]\n",
"\n",
" cp = CANParser(DBC[platform][\"pt\"], messages, CanBus.main)\n",
"\n",
" steering_torque_history = []\n",
" examples = []\n",
"\n",
" for msg in can_msgs:\n",
" cp.update_strings(can_capnp_to_list([msg.as_builder().to_bytes()]))\n",
" steering_torque_history.append(copy.copy(cp.vl[\"Steering_Torque\"]))\n",
"\n",
" steer_warning_last = False\n",
" for i, steering_torque_msg in enumerate(steering_torque_history):\n",
" steer_warning = steering_torque_msg[\"Steer_Warning\"]\n",
"\n",
" steer_angle = steering_torque_msg[\"Steering_Angle\"]\n",
"\n",
" if steer_warning and not steer_warning_last: # positive transition of \"Steer_Warning\"\n",
" examples.append(i)\n",
"\n",
" steer_warning_last = steer_warning\n",
"\n",
" FRAME_DELTA = 100 # plot this many frames around the positive transition\n",
"\n",
" for example in examples:\n",
" fig, axs = plt.subplots(2)\n",
"\n",
" min_frame = int(example-FRAME_DELTA/2)\n",
" max_frame = int(example+FRAME_DELTA/2)\n",
"\n",
" steering_angle_history = [msg[\"Steering_Angle\"] for msg in steering_torque_history[min_frame:max_frame]]\n",
" steering_warning_history = [msg[\"Steer_Warning\"] for msg in steering_torque_history[min_frame:max_frame]]\n",
"\n",
" xs = np.arange(-FRAME_DELTA/2, FRAME_DELTA/2)\n",
"\n",
" axs[0].plot(xs, steering_angle_history)\n",
" axs[0].set_ylabel(\"Steering Angle (deg)\")\n",
" axs[1].plot(xs, steering_warning_history)\n",
" axs[1].set_ylabel(\"Steer Warning\")\n",
"\n",
" plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}