The Track That Forgot Its Past — Python Bug Hunt

Briefing

Modelled on the Uber ATG test-vehicle crash in Tempe, Arizona, March 2018. The NTSB's investigation found that the automated driving system detected the pedestrian several seconds before impact but repeatedly changed its classification of her — between vehicle, bicycle and "other". Each time the classification changed, the system did not use the object's previous tracking history, so it could not form a path prediction for her in time.

This reconstruction's tracker starts a fresh, empty history whenever an object's label changes, even though it is the same track id. An object that keeps being relabelled never accumulates the two observations a motion estimate needs.

Fix Tracker so an object's history survives reclassification.

Bug report

BUG-TRACK-HIST · Priority: Critical (safety) · Reported by: perception review

Tracker, per track_id:

• observe(track_id, label, t, x, y) appends (t, x, y) to that track's history and sets its label to the latest one. A change of label is a reclassification of the SAME object: the history is kept.
• label(track_id) -> the latest label, or None for an unknown id
• predict(track_id, dt) -> [x, y] extrapolated dt seconds past the last observation using motion.velocity(history) (first to last observation), each coordinate rounded to 3 places; None for an unknown id or when velocity is None (fewer than two observations)
• tracks are independent: nothing about one id affects another

Observed: a pedestrian observed for three frames as vehicle, bicycle, other has no prediction at all.

Logs

[perception] track 17 label vehicle -> bicycle (history reset)
[perception] track 17 label bicycle -> other (history reset)
[planner] track 17: no predicted path

The code as shipped

src/perception/tracker.py (editable)

motion = bug_require("./motion.py")


class Tracker:
    def __init__(self):
        self.tracks = {}

    def observe(self, track_id, label, t, x, y):
        track = self.tracks.get(track_id)
        if track is None or track["label"] != label:
            track = {"label": label, "history": []}
            self.tracks[track_id] = track
        track["history"].append((t, x, y))

    def label(self, track_id):
        track = self.tracks.get(track_id)
        return track["label"] if track else None

    def predict(self, track_id, dt):
        track = self.tracks.get(track_id)
        if track is None:
            return None
        v = motion.velocity(track["history"])
        if v is None:
            return None
        t, x, y = track["history"][-1]
        return [round(x + v[0] * dt, 3), round(y + v[1] * dt, 3)]

Read-only context: src/perception/motion.py.