mirror of
https://github.com/zvx-echo6/recon.git
synced 2026-05-20 06:34:40 +02:00
feat(offroute): Phase O2b — WorldCover friction integration, lake avoidance validated
- New friction.py: reads WorldCover friction VRT, resamples to match elevation grid, provides point sampling for validation - Modified cost.py: accepts optional friction array, multiplies Tobler time cost by friction multiplier, inf for water/nodata (255/0) - Modified prototype.py: loads friction layer, passes to cost function, validates path avoids water cells (friction=255) Validated on Idaho test bbox: - Path avoids Murtaugh Lake (no water cells on path) - Friction along path: min=10, max=20, mean=10.2 - Effort increased 3.4% vs Phase O1 due to friction multipliers Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
parent
f2a0f81580
commit
26d4bc7478
3 changed files with 420 additions and 133 deletions
|
|
@ -1,94 +1,132 @@
|
|||
"""
|
||||
Tobler off-path hiking cost function for OFFROUTE.
|
||||
|
||||
Computes travel time cost based on terrain slope using Tobler's
|
||||
hiking function with off-trail penalty.
|
||||
"""
|
||||
import math
|
||||
import numpy as np
|
||||
from typing import Tuple
|
||||
|
||||
# Maximum passable slope in degrees
|
||||
MAX_SLOPE_DEG = 40.0
|
||||
|
||||
# Tobler off-path parameters
|
||||
TOBLER_BASE_SPEED = 6.0
|
||||
TOBLER_OFF_TRAIL_MULT = 0.6
|
||||
|
||||
|
||||
def tobler_speed(grade: float) -> float:
|
||||
"""
|
||||
Calculate hiking speed using Tobler's off-path function.
|
||||
|
||||
speed_kmh = 0.6 * 6.0 * exp(-3.5 * |grade + 0.05|)
|
||||
|
||||
Peak speed is ~3.6 km/h at grade = -0.05 (slight downhill).
|
||||
"""
|
||||
return TOBLER_OFF_TRAIL_MULT * TOBLER_BASE_SPEED * math.exp(-3.5 * abs(grade + 0.05))
|
||||
|
||||
|
||||
def compute_cost_grid(
|
||||
elevation: np.ndarray,
|
||||
cell_size_m: float,
|
||||
cell_size_lat_m: float = None,
|
||||
cell_size_lon_m: float = None
|
||||
) -> np.ndarray:
|
||||
"""
|
||||
Compute isotropic travel cost grid from elevation data.
|
||||
|
||||
Each cell's cost represents the time (in seconds) to traverse that cell,
|
||||
based on the average slope from neighboring cells.
|
||||
"""
|
||||
if cell_size_lat_m is None:
|
||||
cell_size_lat_m = cell_size_m
|
||||
if cell_size_lon_m is None:
|
||||
cell_size_lon_m = cell_size_m
|
||||
|
||||
rows, cols = elevation.shape
|
||||
|
||||
# Compute gradients in both directions
|
||||
dy = np.zeros_like(elevation)
|
||||
dx = np.zeros_like(elevation)
|
||||
|
||||
# Central differences for interior, forward/backward at edges
|
||||
dy[1:-1, :] = (elevation[:-2, :] - elevation[2:, :]) / (2 * cell_size_lat_m)
|
||||
dy[0, :] = (elevation[0, :] - elevation[1, :]) / cell_size_lat_m
|
||||
dy[-1, :] = (elevation[-2, :] - elevation[-1, :]) / cell_size_lat_m
|
||||
|
||||
dx[:, 1:-1] = (elevation[:, 2:] - elevation[:, :-2]) / (2 * cell_size_lon_m)
|
||||
dx[:, 0] = (elevation[:, 1] - elevation[:, 0]) / cell_size_lon_m
|
||||
dx[:, -1] = (elevation[:, -1] - elevation[:, -2]) / cell_size_lon_m
|
||||
|
||||
# Compute slope magnitude (grade = rise/run)
|
||||
grade_magnitude = np.sqrt(dx**2 + dy**2)
|
||||
|
||||
# Convert to slope angle in degrees
|
||||
slope_deg = np.degrees(np.arctan(grade_magnitude))
|
||||
|
||||
# Compute speed for each cell using Tobler function
|
||||
speed_kmh = TOBLER_OFF_TRAIL_MULT * TOBLER_BASE_SPEED * np.exp(-3.5 * np.abs(grade_magnitude + 0.05))
|
||||
|
||||
# Convert speed to time cost (seconds to traverse one cell)
|
||||
avg_cell_size = (cell_size_lat_m + cell_size_lon_m) / 2
|
||||
cost = avg_cell_size * 3.6 / speed_kmh
|
||||
|
||||
# Set impassable cells (slope > MAX_SLOPE_DEG) to infinity
|
||||
cost[slope_deg > MAX_SLOPE_DEG] = np.inf
|
||||
|
||||
# Handle NaN elevations (no data)
|
||||
cost[np.isnan(elevation)] = np.inf
|
||||
|
||||
return cost
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Testing Tobler speed function:")
|
||||
for grade in [-0.3, -0.1, -0.05, 0.0, 0.05, 0.1, 0.3]:
|
||||
speed = tobler_speed(grade)
|
||||
print(f" Grade {grade:+.2f}: {speed:.2f} km/h")
|
||||
|
||||
print("\nTesting cost grid computation:")
|
||||
elev = np.arange(100).reshape(10, 10).astype(np.float32) * 10
|
||||
cost = compute_cost_grid(elev, cell_size_m=30.0)
|
||||
print(f" Elevation range: {elev.min():.0f} - {elev.max():.0f} m")
|
||||
print(f" Cost range: {cost[~np.isinf(cost)].min():.1f} - {cost[~np.isinf(cost)].max():.1f} s")
|
||||
"""
|
||||
Tobler off-path hiking cost function for OFFROUTE.
|
||||
|
||||
Computes travel time cost based on terrain slope using Tobler's
|
||||
hiking function with off-trail penalty. Optionally applies friction
|
||||
multipliers from land cover data.
|
||||
"""
|
||||
import math
|
||||
import numpy as np
|
||||
from typing import Optional
|
||||
|
||||
# Maximum passable slope in degrees
|
||||
MAX_SLOPE_DEG = 40.0
|
||||
|
||||
# Tobler off-path parameters
|
||||
TOBLER_BASE_SPEED = 6.0
|
||||
TOBLER_OFF_TRAIL_MULT = 0.6
|
||||
|
||||
|
||||
def tobler_speed(grade: float) -> float:
|
||||
"""
|
||||
Calculate hiking speed using Tobler's off-path function.
|
||||
|
||||
speed_kmh = 0.6 * 6.0 * exp(-3.5 * |grade + 0.05|)
|
||||
|
||||
Peak speed is ~3.6 km/h at grade = -0.05 (slight downhill).
|
||||
"""
|
||||
return TOBLER_OFF_TRAIL_MULT * TOBLER_BASE_SPEED * math.exp(-3.5 * abs(grade + 0.05))
|
||||
|
||||
|
||||
def compute_cost_grid(
|
||||
elevation: np.ndarray,
|
||||
cell_size_m: float,
|
||||
cell_size_lat_m: float = None,
|
||||
cell_size_lon_m: float = None,
|
||||
friction: Optional[np.ndarray] = None
|
||||
) -> np.ndarray:
|
||||
"""
|
||||
Compute isotropic travel cost grid from elevation data.
|
||||
|
||||
Each cell's cost represents the time (in seconds) to traverse that cell,
|
||||
based on the average slope from neighboring cells.
|
||||
|
||||
Args:
|
||||
elevation: 2D array of elevation values in meters
|
||||
cell_size_m: Average cell size in meters
|
||||
cell_size_lat_m: Cell size in latitude direction (optional)
|
||||
cell_size_lon_m: Cell size in longitude direction (optional)
|
||||
friction: Optional 2D array of friction multipliers.
|
||||
Values should be float (1.0 = baseline, 2.0 = 2x slower).
|
||||
np.inf marks impassable cells.
|
||||
If None, no friction is applied (backward compatible).
|
||||
|
||||
Returns:
|
||||
2D array of travel cost in seconds per cell.
|
||||
np.inf for impassable cells.
|
||||
"""
|
||||
if cell_size_lat_m is None:
|
||||
cell_size_lat_m = cell_size_m
|
||||
if cell_size_lon_m is None:
|
||||
cell_size_lon_m = cell_size_m
|
||||
|
||||
rows, cols = elevation.shape
|
||||
|
||||
# Compute gradients in both directions
|
||||
dy = np.zeros_like(elevation)
|
||||
dx = np.zeros_like(elevation)
|
||||
|
||||
# Central differences for interior, forward/backward at edges
|
||||
dy[1:-1, :] = (elevation[:-2, :] - elevation[2:, :]) / (2 * cell_size_lat_m)
|
||||
dy[0, :] = (elevation[0, :] - elevation[1, :]) / cell_size_lat_m
|
||||
dy[-1, :] = (elevation[-2, :] - elevation[-1, :]) / cell_size_lat_m
|
||||
|
||||
dx[:, 1:-1] = (elevation[:, 2:] - elevation[:, :-2]) / (2 * cell_size_lon_m)
|
||||
dx[:, 0] = (elevation[:, 1] - elevation[:, 0]) / cell_size_lon_m
|
||||
dx[:, -1] = (elevation[:, -1] - elevation[:, -2]) / cell_size_lon_m
|
||||
|
||||
# Compute slope magnitude (grade = rise/run)
|
||||
grade_magnitude = np.sqrt(dx**2 + dy**2)
|
||||
|
||||
# Convert to slope angle in degrees
|
||||
slope_deg = np.degrees(np.arctan(grade_magnitude))
|
||||
|
||||
# Compute speed for each cell using Tobler function
|
||||
speed_kmh = TOBLER_OFF_TRAIL_MULT * TOBLER_BASE_SPEED * np.exp(-3.5 * np.abs(grade_magnitude + 0.05))
|
||||
|
||||
# Convert speed to time cost (seconds to traverse one cell)
|
||||
avg_cell_size = (cell_size_lat_m + cell_size_lon_m) / 2
|
||||
cost = avg_cell_size * 3.6 / speed_kmh
|
||||
|
||||
# Set impassable cells (slope > MAX_SLOPE_DEG) to infinity
|
||||
cost[slope_deg > MAX_SLOPE_DEG] = np.inf
|
||||
|
||||
# Handle NaN elevations (no data)
|
||||
cost[np.isnan(elevation)] = np.inf
|
||||
|
||||
# Apply friction multipliers if provided
|
||||
if friction is not None:
|
||||
if friction.shape != elevation.shape:
|
||||
raise ValueError(
|
||||
f"Friction shape {friction.shape} does not match elevation shape {elevation.shape}"
|
||||
)
|
||||
# Multiply cost by friction (inf * anything = inf, which is correct)
|
||||
cost = cost * friction
|
||||
|
||||
return cost
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Testing Tobler speed function:")
|
||||
for grade in [-0.3, -0.1, -0.05, 0.0, 0.05, 0.1, 0.3]:
|
||||
speed = tobler_speed(grade)
|
||||
print(f" Grade {grade:+.2f}: {speed:.2f} km/h")
|
||||
|
||||
print("\nTesting cost grid computation (no friction):")
|
||||
elev = np.arange(100).reshape(10, 10).astype(np.float32) * 10
|
||||
cost = compute_cost_grid(elev, cell_size_m=30.0)
|
||||
print(f" Elevation range: {elev.min():.0f} - {elev.max():.0f} m")
|
||||
finite = cost[~np.isinf(cost)]
|
||||
if len(finite) > 0:
|
||||
print(f" Cost range: {finite.min():.1f} - {finite.max():.1f} s")
|
||||
else:
|
||||
print(f" All cells impassable (test data too steep)")
|
||||
|
||||
print("\nTesting cost grid with friction:")
|
||||
elev = np.ones((10, 10), dtype=np.float32) * 1000 # flat terrain
|
||||
friction = np.ones((10, 10), dtype=np.float32) * 1.5 # 1.5x friction
|
||||
friction[5, 5] = np.inf # one impassable cell
|
||||
cost = compute_cost_grid(elev, cell_size_m=30.0, friction=friction)
|
||||
print(f" Base cost (flat, 30m cell): {30 * 3.6 / (0.6 * 6.0 * np.exp(-3.5 * 0.05)):.1f} s")
|
||||
print(f" With 1.5x friction: {cost[0, 0]:.1f} s")
|
||||
print(f" Impassable cells: {np.sum(np.isinf(cost))}")
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue