fix: smooth GPS-derived replay speed to kill jitter spikes

route_points (Pi) and get_trip_route (server) derived GPS speed from a
single 5s segment, so GPS position jitter could read 150+ km/h when the car
wasn't going that fast. Both now average over a trailing ~30s window (same
as the max-speed calc), so spikes are damped.
This commit is contained in:
Mathieu Moran
2026-08-15 17:38:45 -04:00
parent 2817930bdc
commit bfc8ddabd9
2 changed files with 37 additions and 14 deletions
+22 -6
View File
@@ -285,12 +285,28 @@ def route_points(raw_rows, max_points=2000, odometer_baseline=0.0, prior_km=0.0)
for index, row in enumerate(rows): for index, row in enumerate(rows):
row["speed_source"] = "obd" if row["speed"] > 0 else "gps" row["speed_source"] = "obd" if row["speed"] > 0 else "gps"
if row["speed"] <= 0 and index: if row["speed"] <= 0 and index:
distance_km, segment_speed = _segment(row, rows[index - 1]) # Derive GPS speed over a trailing ~30s window, not the raw 5s
row["speed"] = ( # segment — a single segment can spike 100+ km/h on GPS jitter
segment_speed # (same smoothing build_trip_summaries uses for max speed).
if distance_km * 1000 >= GPS_MOTION_METERS window_start = max(0, index - GPS_SPEED_WINDOW)
else 0 start_row = rows[window_start]
) seconds = (
row["datetime"] - start_row["datetime"]
).total_seconds()
if seconds > 0:
window_km = haversine_km(
(start_row["latitude"], start_row["longitude"]),
(row["latitude"], row["longitude"]),
)
window_speed = window_km / seconds * 3600
row["speed"] = (
window_speed
if window_km * 1000 >= GPS_MOTION_METERS
and window_speed <= MAX_PLAUSIBLE_SPEED_KMH
else 0
)
else:
row["speed"] = 0
if index: if index:
segment_km, _ = _segment(row, rows[index - 1]) segment_km, _ = _segment(row, rows[index - 1])
cumulative_km += segment_km cumulative_km += segment_km
+15 -8
View File
@@ -625,6 +625,7 @@ def get_trip_route(device_id, trip_id):
result_points = [] result_points = []
cumulative = 0.0 cumulative = 0.0
prev = None prev = None
gps_window = [] # trailing (lat, lon, datetime) points for GPS speed smoothing
for p in points: for p in points:
lat = float(p[1]) lat = float(p[1])
lon = float(p[2]) lon = float(p[2])
@@ -632,18 +633,24 @@ def get_trip_route(device_id, trip_id):
raw_odo = p[4] raw_odo = p[4]
speed_source = "obd" if speed > 0 else "gps" speed_source = "obd" if speed > 0 else "gps"
# Mirror the Pi's route_points GPS-speed fallback: when OBD speed is # Mirror the Pi's route_points GPS-speed fallback: when OBD speed is
# missing (adapter dropout), derive speed from the previous point's # missing (adapter dropout), derive speed from a trailing ~30s window
# movement so the replay doesn't flatline at 0 km/h while the car moves. # of movement (not the previous point) so the replay doesn't flatline
if speed <= 0 and prev is not None: # at 0 km/h while the car moves — and a single jittery 5s segment can't
seconds = (p[0] - prev[2]).total_seconds() # spike the readout.
if speed <= 0 and gps_window:
start = gps_window[0]
seconds = (p[0] - start[2]).total_seconds()
if seconds > 0: if seconds > 0:
dist_km = hav(prev[0], prev[1], lat, lon) dist_km = hav(start[0], start[1], lat, lon)
seg_speed = dist_km / seconds * 3600 w_speed = dist_km / seconds * 3600
if seg_speed <= 220 and dist_km * 1000 >= 8: if w_speed <= 220 and dist_km * 1000 >= 8:
speed = seg_speed speed = w_speed
if prev is not None: if prev is not None:
cumulative += hav(prev[0], prev[1], lat, lon) cumulative += hav(prev[0], prev[1], lat, lon)
prev = (lat, lon, p[0]) prev = (lat, lon, p[0])
gps_window.append((lat, lon, p[0]))
if len(gps_window) > 6:
gps_window.pop(0)
if raw_odo is not None and float(raw_odo) > 0: if raw_odo is not None and float(raw_odo) > 0:
odometer = float(raw_odo) odometer = float(raw_odo)
else: else: