Moto Trackday Project Script Auto Race Inf M Verified Direct

Once your script detects this rastructure, you can auto-split lap times into sectors without manual timing gates. Part 3: The "M Verified" Standard – Why Meters Matter GPS errors of 2–5 meters are common. Over a lap, that means your "lap length" might vary by 10 meters – enough to make time comparisons useless.

print(f"Auto-detected len(corner_meters) corners at meters: corner_meters") return corner_meters detect_corners("my_lap.gpx") To verify distance, compare GPS against wheel speed sensor (WSS) pulses: moto trackday project script auto race inf m verified

Within one season, you’ll stop riding by feel alone. You’ll ride by – and drop seconds off your lap time. Have you built a trackday script? Share your GitHub or RaceStudio template in the comments. Let’s verify every meter, together. Once your script detects this rastructure, you can

pip install gpxpy geopy numpy scipy matplotlib pandas Here’s a simplified script skeleton that detects corner entries based on yaw rate (GPS-derived heading change): Share your GitHub or RaceStudio template in the comments

# Extract points and heading headings = [] for pt in gpx.tracks[0].segments[0].points: headings.append(pt.course) # degrees

import gpxpy import numpy as np from scipy.signal import find_peaks def detect_corners(gpx_file): with open(gpx_file, 'r') as f: gpx = gpxpy.parse(f)

corner_meters = [] for peak in peaks: cumulative_dist = 0 for i, pt in enumerate(gpx.tracks[0].segments[0].points): if i <= peak: cumulative_dist += pt.distance_2d(prev_pt) prev_pt = pt corner_meters.append(round(cumulative_dist, 1))