json_data.json

{
  "Rules": {
    "Rules": [
      {
        "rule_id": "R1",
        "priority": 1,
        "text": "A trajectory state (x,y) is inside a zone if xmin <= x <= xmax AND ymin <= y <= ymax.",
        "scope": "global"
      },
      {
        "rule_id": "R2",
        "priority": 2,
        "text": "Weighted risk contribution for a zone = zone_risk * count_in_zone.",
        "scope": "global"
      },
      {
        "rule_id": "R3",
        "priority": 3,
        "text": "Total risk = sum over zones of (zone_risk * count_in_zone).",
        "scope": "global"
      },
      {
        "rule_id": "R4",
        "priority": 4,
        "text": "The candidate with the LOWEST total risk should receive the HIGHEST safety_score.",
        "scope": "global"
      },
      {
        "rule_id": "R5",
        "priority": 5,
        "text": "If two candidates have identical total risk, break ties in this order: fewer total in-zone states across all zones, fewer trajectory states (shorter path), fewer turns (direction changes between segments).",
        "scope": "global"
      }
    ]
  },
  "CandidateEvals": {
    "evaluations": [
      {
        "candidate_id": "traj_1_diagonal",
        "safety_score": 2.0,
        "justification": "High exposure to zone_2 (risk=0.8) and zone_1 (risk=0.25)",
        "violations": [
          "R4"
        ]
      },
      {
        "candidate_id": "traj_2_bottom_then_up",
        "safety_score": 5.0,
        "justification": "Moderate exposure to both zones, but fewer in-zone states than traj_1_diagonal",
        "violations": []
      },
      {
        "candidate_id": "traj_3_left_then_right",
        "safety_score": 8.0,
        "justification": "Lowest total risk among all candidates",
        "violations": []
      }
    ]
  }
}