Simulation for Unknown Scenarios

"""Adversarial scenario generation to discover unknown SOTIF failures."""
import random

def generate_adversarial_aeb_scenario(base_scenario: dict,
                                        n_variations: int = 100) -> list:
    """
    Generate adversarial variations of a base scenario.
    Perturbs parameters to find AEB detection boundaries.
    """
    adversarial = []

    for _ in range(n_variations):
        sc = base_scenario.copy()

        # Perturb: contrast (find minimum contrast where detection fails)
        sc["target_contrast"] = random.uniform(0.05, 0.4)

        # Perturb: partial occlusion
        sc["target_occlusion_pct"] = random.uniform(0, 80)

        # Perturb: rain intensity near ODD boundary
        sc["rain_mmh"] = random.uniform(0, 8)

        # Perturb: target colour in problematic range
        sc["target_colour_hsv_v"] = random.uniform(0.8, 1.0)  # bright

        # Perturb: multiple simultaneous adverse conditions
        if random.random() < 0.2:
            sc["sun_angle_deg"] = random.uniform(5, 25)  # glare
            sc["rain_mmh"] = random.uniform(1, 3)
            # Combined: moderate rain + glare (interaction effect)

        adversarial.append(sc)

    return adversarial

base = {
    "ego_speed_kmh": 50,
    "target_dist_m": 35,
    "target_type":   "pedestrian",
    "lighting":      "daylight"
}
scenarios = generate_adversarial_aeb_scenario(base, n_variations=500)
print(f"Generated {len(scenarios)} adversarial scenarios")
print("Run in CARLA/CarMaker to find detection boundary...")