File size: 7,688 Bytes
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import json
import logging
import psutil
import argparse
import math
from pathlib import Path
import numpy as np
from multiprocessing import Pool, cpu_count
from tqdm import tqdm
logging.basicConfig(level=logging.INFO)
def check_uturn(headings, valid_mask):
"""
Check if a vehicle makes a U-turn by comparing heading angles.
Args:
headings: List of heading angles in radians
valid_mask: List of boolean values indicating valid timesteps
Returns:
bool: True if U-turn detected
"""
# Convert 150 degrees to radians (150 * pi/180)
angle_threshold = 2.618 # approximately 150 degrees in radians
# Get first valid heading
valid_indices = [i for i, v in enumerate(valid_mask) if v]
if not valid_indices:
return False
first_valid_idx = valid_indices[0]
first_heading = headings[first_valid_idx]
# Check subsequent valid headings
for i in valid_indices[1:]:
angle_diff = abs(headings[i] - first_heading)
# Normalize angle difference to [-pi, pi]
angle_diff = (angle_diff + math.pi) % (2 * math.pi) - math.pi
if abs(angle_diff) > angle_threshold:
return True
return False
def check_reversing(headings, velocities, valid_mask, min_timesteps=10):
"""
Check if a vehicle reverses by comparing velocity direction with heading.
Args:
headings: List of heading angles in radians
velocities: List of dictionaries containing 'x' and 'y' velocities
valid_mask: List of boolean values indicating valid timesteps
min_timesteps: Minimum number of consecutive timesteps required for reversing
Returns:
bool: True if sustained reversing detected
"""
# Convert angle range to radians (150 to 210 degrees)
min_angle = 2.618 # 150 degrees
consecutive_reverse = 0
for i, valid in enumerate(valid_mask):
if not valid:
consecutive_reverse = 0
continue
# Calculate velocity direction
vx = velocities[i]['x']
vy = velocities[i]['y']
# Skip stationary moments
if abs(vx) < 0.1 and abs(vy) < 0.1:
consecutive_reverse = 0
continue
velocity_angle = math.atan2(vy, vx)
heading = headings[i]
# Calculate angle between velocity and heading
angle_diff = velocity_angle - heading
# Normalize to [-pi, pi]
angle_diff = (angle_diff + math.pi) % (2 * math.pi) - math.pi
# Check if velocity is in the reverse cone
if min_angle <= abs(angle_diff):
consecutive_reverse += 1
if consecutive_reverse >= min_timesteps:
return True
else:
consecutive_reverse = 0
return False
def process_scene(args):
"""Process a single scene file."""
filepath, min_reverse_timesteps = args
try:
with open(filepath, 'r') as f:
scene = json.load(f)
uturn_count = np.int64(0)
reverse_count = np.int64(0)
total_agents = np.int64(0)
# Process each object
for obj in scene['objects']:
# Check if object is a vehicle or cyclist and not an expert
if (obj['type'] in ['vehicle', 'cyclist'] and
not obj.get('mark_as_expert', False)):
total_agents += 1
# Get valid mask and corresponding headings/velocities
valid_mask = obj['valid']
headings = obj['heading']
velocities = obj['velocity']
# Check for U-turn
if check_uturn(headings, valid_mask):
uturn_count += 1
# Check for reversing
if check_reversing(headings, velocities, valid_mask, min_reverse_timesteps):
reverse_count += 1
return filepath, (total_agents, uturn_count, reverse_count)
except Exception as e:
logging.error(f"Error processing {filepath}: {e}")
return filepath, None
def process_directory(args):
"""Process all JSON files in directory."""
input_dir = Path(args.input_dir)
num_workers = args.num_workers
# Get all JSON files
json_files = list(input_dir.glob("*.json"))
if not json_files:
logging.error(f"No JSON files found in {input_dir}")
return
logging.info(f"Found {len(json_files)} JSON files to process")
# Calculate batch size based on available memory
mem_info = psutil.virtual_memory()
available_memory = mem_info.available / (1024**3) # Convert to GB
usable_memory = int(available_memory * 0.9) # Use 90% of available memory
batch_size = min(1000 * usable_memory, len(json_files))
# Initialize counters using numpy int64 to handle large numbers
total_processed = np.int64(0)
total_agents = np.int64(0)
total_uturns = np.int64(0)
total_reverses = np.int64(0)
# Process files in batches
for i in range(0, len(json_files), int(batch_size)):
batch = json_files[i:i + int(batch_size)]
# Process batch in parallel
with Pool(num_workers) as pool:
results = list(tqdm(
pool.imap(process_scene, [(str(f), args.min_reverse_timesteps) for f in batch]),
total=len(batch),
desc=f"Processing batch {i//int(batch_size) + 1}"
))
# Count results
for filepath, counts in results:
if counts is not None:
agents, uturns, reverses = counts
total_processed += 1
total_agents += agents
total_uturns += uturns
total_reverses += reverses
# Calculate percentages using float64 for precision
uturn_percentage = (float(total_uturns) / float(total_agents) * 100) if total_agents > 0 else 0.0
reverse_percentage = (float(total_reverses) / float(total_agents) * 100) if total_agents > 0 else 0.0
logging.info(f"Processing complete!")
logging.info(f"Total files processed: {total_processed:,d}")
logging.info(f"Total non-expert agents: {total_agents:,d}")
logging.info(f"Total U-turns: {total_uturns:,d} ({uturn_percentage:.2f}%)")
logging.info(f"Total reversing: {total_reverses:,d} ({reverse_percentage:.2f}%)")
# Also save results to a JSON file for future reference
results = {
"total_files_processed": int(total_processed),
"total_non_expert_agents": int(total_agents),
"total_uturns": int(total_uturns),
"total_reversing": int(total_reverses),
"uturn_percentage": float(uturn_percentage),
"reverse_percentage": float(reverse_percentage)
}
with open('vehicle_behavior_results.json', 'w') as f:
json.dump(results, f, indent=4)
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Analyze vehicle behaviors in JSON files"
)
parser.add_argument(
"input_dir",
help="Directory containing JSON files to process"
)
parser.add_argument(
"--num_workers",
type=int,
default=cpu_count(),
help="Number of worker processes (default: number of CPU cores)"
)
parser.add_argument(
"--min_reverse_timesteps",
type=int,
default=3,
help="Minimum number of consecutive timesteps required for reversing (default: 3)"
)
args = parser.parse_args()
process_directory(args) |