FA-68146 / Traffic signal timing plans / Open access

Uniform delay level of service: LOS thresholds are exclusive · case 01

Uniform delay level of service returns a wrong result when lOS thresholds are exclusive.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

A delay exactly at a threshold such as 20.0 s is graded one level worse.

VERIFIED REPAIR

Restore the LOS threshold comparison rule so that the step reads `if tenths <= lim:`.

Unsuccessful approach: Comparing delay seconds against thresholds in tenths grades almost every movement A.

Case contract

Input {cycle, green, volume, sat_per_lane, lanes}. lam = green/cycle, capacity = sat*lanes*lam, X = volume/capacity, uniform delay d = 0.5*C*(1-lam)^2/(1 - min(1,X)*lam) rounded half up to tenths. LOS thresholds on tenths: <=100 A, <=200 B, <=350 C, <=550 D, <=800 E, else F; any X > 1 is F. Return {vc_milli: floor(1000X), delay_tenths, los}.

Why this case matters

Signal timing arithmetic is exact and integer or rational; a wrong rule silently produces unsafe or inefficient timing plans.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(x):
    C, g = x['cycle'], x['green']
    lam = Fraction(g, C)
    cap = x['sat_per_lane'] * x['lanes'] * lam
    X = Fraction(x['volume']) / cap
    d = Fraction(1, 2) * C * (1 - lam) ** 2 / (1 - min(1, X) * lam)
    tenths = int(d * 10 + Fraction(1, 2))
    if X > 1:
        los = 'F'
    else:
        los = 'F'
        for lim, lab in ((100, 'A'), (200, 'B'), (350, 'C'), (550, 'D'), (800, 'E')):
            if tenths < lim:
                los = lab
                break
    return {'vc_milli': int(X * 1000), 'delay_tenths': tenths, 'los': los}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 123, 'volume': 3014, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1021, 'delay_tenths': 135, 'los': 'F'}), ({'cycle': 120, 'green': 23, 'volume': 782, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1200, 'delay_tenths': 485, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 110, 'green': 84, 'volume': 4598, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1770, 'delay_tenths': 130, 'los': 'F'}), ({'cycle': 150, 'green': 80, 'volume': 2720, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 120, 'green': 50, 'volume': 2125, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 19, 'volume': 507, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 784, 'delay_tenths': 635, 'los': 'E'}), ({'cycle': 70, 'green': 47, 'volume': 2082, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 912, 'delay_tenths': 97, 'los': 'A'}), ({'cycle': 100, 'green': 29, 'volume': 1805, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1728, 'delay_tenths': 355, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 140, 'green': 76, 'volume': 1466, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1500, 'delay_tenths': 320, 'los': 'F'}), ({'cycle': 80, 'green': 25, 'volume': 1080, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1920, 'delay_tenths': 275, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'})], [({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 60, 'green': 29, 'volume': 1124, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 407, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 90, 'green': 71, 'volume': 5771, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1354, 'delay_tenths': 95, 'los': 'F'}), ({'cycle': 90, 'green': 66, 'volume': 6108, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1633, 'delay_tenths': 120, 'los': 'F'}), ({'cycle': 90, 'green': 20, 'volume': 2234, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1971, 'delay_tenths': 350, 'los': 'F'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 140, 'green': 108, 'volume': 3411, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1300, 'delay_tenths': 160, 'los': 'F'})], [({'cycle': 110, 'green': 70, 'volume': 6812, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1982, 'delay_tenths': 200, 'los': 'F'}), ({'cycle': 80, 'green': 49, 'volume': 625, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 600, 'delay_tenths': 95, 'los': 'A'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 90, 'green': 25, 'volume': 383, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 766, 'delay_tenths': 298, 'los': 'C'}), ({'cycle': 150, 'green': 23, 'volume': 434, 'sat_per_lane': 1900, 'lanes': 1}, {'vc_milli': 1489, 'delay_tenths': 635, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 100, 'green': 81, 'volume': 2684, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 974, 'delay_tenths': 86, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 100, 'green': 82, 'volume': 911, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 653, 'delay_tenths': 35, 'los': 'A'}), ({'cycle': 120, 'green': 10, 'volume': 475, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 550, 'los': 'D'}), ({'cycle': 130, 'green': 85, 'volume': 4393, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1244, 'delay_tenths': 225, 'los': 'F'}), ({'cycle': 90, 'green': 55, 'volume': 1084, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 521, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 120, 'green': 40, 'volume': 1300, 'sat_per_lane': 1900, 'lanes': 2}, {'vc_milli': 1026, 'delay_tenths': 400, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'})]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check('timing oracle' + ' %d' % i, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
timing oracle 0	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	Passed
timing oracle 1	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	Passed
timing oracle 2	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	Passed
timing oracle 3	`{'delay_tenths': 250, 'los': 'C', 'vc_milli': 1000}`	`{'delay_tenths': 250, 'los': 'C', 'vc_milli': 1000}`	Passed
timing oracle 4	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	Passed
timing oracle 5	`{'delay_tenths': 350, 'los': 'D', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Failed
timing oracle 6	`{'delay_tenths': 350, 'los': 'D', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Failed
timing oracle 7	`{'delay_tenths': 200, 'los': 'C', 'vc_milli': 750}`	`{'delay_tenths': 200, 'los': 'B', 'vc_milli': 750}`	Failed

SHA-256 / 6468f538da819f3b3554d40626beca3cfda2eefbc83ab5057a886df21f101f0d

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(x):
    C, g = x['cycle'], x['green']
    lam = Fraction(g, C)
    cap = x['sat_per_lane'] * x['lanes'] * lam
    X = Fraction(x['volume']) / cap
    d = Fraction(1, 2) * C * (1 - lam) ** 2 / (1 - min(1, X) * lam)
    tenths = int(d * 10 + Fraction(1, 2))
    if X > 1:
        los = 'F'
    else:
        los = 'F'
        for lim, lab in ((100, 'A'), (200, 'B'), (350, 'C'), (550, 'D'), (800, 'E')):
            if d <= lim:
                los = lab
                break
    return {'vc_milli': int(X * 1000), 'delay_tenths': tenths, 'los': los}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 123, 'volume': 3014, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1021, 'delay_tenths': 135, 'los': 'F'}), ({'cycle': 120, 'green': 23, 'volume': 782, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1200, 'delay_tenths': 485, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 110, 'green': 84, 'volume': 4598, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1770, 'delay_tenths': 130, 'los': 'F'}), ({'cycle': 150, 'green': 80, 'volume': 2720, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 120, 'green': 50, 'volume': 2125, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 19, 'volume': 507, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 784, 'delay_tenths': 635, 'los': 'E'}), ({'cycle': 70, 'green': 47, 'volume': 2082, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 912, 'delay_tenths': 97, 'los': 'A'}), ({'cycle': 100, 'green': 29, 'volume': 1805, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1728, 'delay_tenths': 355, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 140, 'green': 76, 'volume': 1466, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1500, 'delay_tenths': 320, 'los': 'F'}), ({'cycle': 80, 'green': 25, 'volume': 1080, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1920, 'delay_tenths': 275, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'})], [({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 60, 'green': 29, 'volume': 1124, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 407, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 90, 'green': 71, 'volume': 5771, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1354, 'delay_tenths': 95, 'los': 'F'}), ({'cycle': 90, 'green': 66, 'volume': 6108, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1633, 'delay_tenths': 120, 'los': 'F'}), ({'cycle': 90, 'green': 20, 'volume': 2234, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1971, 'delay_tenths': 350, 'los': 'F'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 140, 'green': 108, 'volume': 3411, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1300, 'delay_tenths': 160, 'los': 'F'})], [({'cycle': 110, 'green': 70, 'volume': 6812, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1982, 'delay_tenths': 200, 'los': 'F'}), ({'cycle': 80, 'green': 49, 'volume': 625, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 600, 'delay_tenths': 95, 'los': 'A'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 90, 'green': 25, 'volume': 383, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 766, 'delay_tenths': 298, 'los': 'C'}), ({'cycle': 150, 'green': 23, 'volume': 434, 'sat_per_lane': 1900, 'lanes': 1}, {'vc_milli': 1489, 'delay_tenths': 635, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 100, 'green': 81, 'volume': 2684, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 974, 'delay_tenths': 86, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 100, 'green': 82, 'volume': 911, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 653, 'delay_tenths': 35, 'los': 'A'}), ({'cycle': 120, 'green': 10, 'volume': 475, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 550, 'los': 'D'}), ({'cycle': 130, 'green': 85, 'volume': 4393, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1244, 'delay_tenths': 225, 'los': 'F'}), ({'cycle': 90, 'green': 55, 'volume': 1084, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 521, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 120, 'green': 40, 'volume': 1300, 'sat_per_lane': 1900, 'lanes': 2}, {'vc_milli': 1026, 'delay_tenths': 400, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'})]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check('timing oracle' + ' %d' % i, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
timing oracle 0	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	Passed
timing oracle 1	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	Passed
timing oracle 2	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	Passed
timing oracle 3	`{'delay_tenths': 250, 'los': 'A', 'vc_milli': 1000}`	`{'delay_tenths': 250, 'los': 'C', 'vc_milli': 1000}`	Failed
timing oracle 4	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	Passed
timing oracle 5	`{'delay_tenths': 350, 'los': 'A', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Failed
timing oracle 6	`{'delay_tenths': 350, 'los': 'A', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Failed
timing oracle 7	`{'delay_tenths': 200, 'los': 'A', 'vc_milli': 750}`	`{'delay_tenths': 200, 'los': 'B', 'vc_milli': 750}`	Failed

SHA-256 / 5a69d1b34f22e501a4cb134eecadf45e7861069209d4b734f66dde99331171a8

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(x):
    C, g = x['cycle'], x['green']
    lam = Fraction(g, C)
    cap = x['sat_per_lane'] * x['lanes'] * lam
    X = Fraction(x['volume']) / cap
    d = Fraction(1, 2) * C * (1 - lam) ** 2 / (1 - min(1, X) * lam)
    tenths = int(d * 10 + Fraction(1, 2))
    if X > 1:
        los = 'F'
    else:
        los = 'F'
        for lim, lab in ((100, 'A'), (200, 'B'), (350, 'C'), (550, 'D'), (800, 'E')):
            if tenths <= lim:
                los = lab
                break
    return {'vc_milli': int(X * 1000), 'delay_tenths': tenths, 'los': los}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 123, 'volume': 3014, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1021, 'delay_tenths': 135, 'los': 'F'}), ({'cycle': 120, 'green': 23, 'volume': 782, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1200, 'delay_tenths': 485, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 110, 'green': 84, 'volume': 4598, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1770, 'delay_tenths': 130, 'los': 'F'}), ({'cycle': 150, 'green': 80, 'volume': 2720, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 120, 'green': 50, 'volume': 2125, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 350, 'los': 'C'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 60, 'green': 40, 'volume': 800, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 666, 'delay_tenths': 60, 'los': 'A'}), ({'cycle': 150, 'green': 19, 'volume': 507, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 784, 'delay_tenths': 635, 'los': 'E'}), ({'cycle': 70, 'green': 47, 'volume': 2082, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 912, 'delay_tenths': 97, 'los': 'A'}), ({'cycle': 100, 'green': 29, 'volume': 1805, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 1728, 'delay_tenths': 355, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 140, 'green': 76, 'volume': 1466, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1500, 'delay_tenths': 320, 'los': 'F'}), ({'cycle': 80, 'green': 25, 'volume': 1080, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1920, 'delay_tenths': 275, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'})], [({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 60, 'green': 29, 'volume': 1124, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 407, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 90, 'green': 71, 'volume': 5771, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1354, 'delay_tenths': 95, 'los': 'F'}), ({'cycle': 90, 'green': 66, 'volume': 6108, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1633, 'delay_tenths': 120, 'los': 'F'}), ({'cycle': 90, 'green': 20, 'volume': 2234, 'sat_per_lane': 1700, 'lanes': 3}, {'vc_milli': 1971, 'delay_tenths': 350, 'los': 'F'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 140, 'green': 108, 'volume': 3411, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 1300, 'delay_tenths': 160, 'los': 'F'})], [({'cycle': 110, 'green': 70, 'volume': 6812, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1982, 'delay_tenths': 200, 'los': 'F'}), ({'cycle': 80, 'green': 49, 'volume': 625, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 600, 'delay_tenths': 95, 'los': 'A'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'}), ({'cycle': 90, 'green': 25, 'volume': 383, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 766, 'delay_tenths': 298, 'los': 'C'}), ({'cycle': 150, 'green': 23, 'volume': 434, 'sat_per_lane': 1900, 'lanes': 1}, {'vc_milli': 1489, 'delay_tenths': 635, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 100, 'green': 81, 'volume': 2684, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 974, 'delay_tenths': 86, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'})], [({'cycle': 100, 'green': 82, 'volume': 911, 'sat_per_lane': 1700, 'lanes': 1}, {'vc_milli': 653, 'delay_tenths': 35, 'los': 'A'}), ({'cycle': 120, 'green': 10, 'volume': 475, 'sat_per_lane': 1900, 'lanes': 3}, {'vc_milli': 1000, 'delay_tenths': 550, 'los': 'D'}), ({'cycle': 130, 'green': 85, 'volume': 4393, 'sat_per_lane': 1800, 'lanes': 3}, {'vc_milli': 1244, 'delay_tenths': 225, 'los': 'F'}), ({'cycle': 90, 'green': 55, 'volume': 1084, 'sat_per_lane': 1700, 'lanes': 2}, {'vc_milli': 521, 'delay_tenths': 100, 'los': 'A'}), ({'cycle': 100, 'green': 50, 'volume': 675, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 750, 'delay_tenths': 200, 'los': 'B'}), ({'cycle': 120, 'green': 40, 'volume': 1300, 'sat_per_lane': 1900, 'lanes': 2}, {'vc_milli': 1026, 'delay_tenths': 400, 'los': 'F'}), ({'cycle': 100, 'green': 50, 'volume': 900, 'sat_per_lane': 1800, 'lanes': 1}, {'vc_milli': 1000, 'delay_tenths': 250, 'los': 'C'}), ({'cycle': 90, 'green': 30, 'volume': 700, 'sat_per_lane': 1800, 'lanes': 2}, {'vc_milli': 583, 'delay_tenths': 248, 'los': 'C'})]]
for i, (args, expected) in enumerate(fixtures[N-1]):
    check('timing oracle' + ' %d' % i, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
timing oracle 0	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	`{'delay_tenths': 60, 'los': 'A', 'vc_milli': 666}`	Passed
timing oracle 1	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	`{'delay_tenths': 135, 'los': 'F', 'vc_milli': 1021}`	Passed
timing oracle 2	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	`{'delay_tenths': 485, 'los': 'F', 'vc_milli': 1200}`	Passed
timing oracle 3	`{'delay_tenths': 250, 'los': 'C', 'vc_milli': 1000}`	`{'delay_tenths': 250, 'los': 'C', 'vc_milli': 1000}`	Passed
timing oracle 4	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	`{'delay_tenths': 130, 'los': 'F', 'vc_milli': 1770}`	Passed
timing oracle 5	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Passed
timing oracle 6	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	`{'delay_tenths': 350, 'los': 'C', 'vc_milli': 1000}`	Passed
timing oracle 7	`{'delay_tenths': 200, 'los': 'B', 'vc_milli': 750}`	`{'delay_tenths': 200, 'los': 'B', 'vc_milli': 750}`	Passed

SHA-256 / 93b5bf9e515250e33b5db817dd4a0b16e5993103ab67ea4fab7b9e1e7536a7f7

Verification & scope

A deterministic, bounded toy model with a stipulated contract; it makes no claim of conformance to any agency manual or standard. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-29T14:47:59.527596+00:00.

Case digest / 25f9ae2659e4cc47afa055a445d9e4b9c2ed2a387baa71a2b4b034fc068be3dc