"""
座舱CO₂浓度仿真 + DMS融合

场景：4人长途驾驶，空调内循环
模拟：CO₂积累 → 驾驶员警觉性下降 → DMS检测变化

关键问题：
- DMS检测到PERCLOS上升→判定疲劳
- 但实际根因是CO₂浓度过高→空气质量导致嗜睡
- 解决方案：DMS + CO₂传感器融合 → 精准判定
"""

import numpy as np
from dataclasses import dataclass
from typing import Tuple

@dataclass
class CabinEnvironment:
    """座舱环境参数"""
    num_occupants: int = 1
    cabin_volume_m3: float = 3.0  # 典型轿车座舱体积
    co2_production_rate: float = 0.005  # L/s per person (呼出CO₂)
    ventilation_rate: float = 0.0  # L/s (内循环=0, 外循环~20)
    initial_co2_ppm: float = 400.0  # 初始CO₂浓度
    temperature_c: float = 22.0  # 座舱温度
    humidity_pct: float = 50.0  # 湿度
    
def simulate_cabin_co2(
    env: CabinEnvironment, 
    duration_minutes: float = 120
) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
    """
    仿真座舱CO₂浓度变化
    
    物理模型：
    dC/dt = (P × N) / V - (Q × (C - C_out)) / V
    
    其中：
    C = CO₂浓度(ppm)
    P = 每人CO₂产生率(L/s)
    N = 人数
    V = 座舱体积(m³)
    Q = 通风量(L/s)
    C_out = 外界CO₂浓度(~400ppm)
    
    Returns:
        time: 时间序列(min)
        co2: CO₂浓度序列(ppm)
        alertness: 驾驶员警觉性(0-1)
    """
    dt = 0.1  # 分钟
    t = np.arange(0, duration_minutes, dt)
    
    co2 = np.zeros_like(t)
    co2[0] = env.initial_co2_ppm
    alertness = np.ones_like(t)
    
    # 转换单位
    V_L = env.cabin_volume_m3 * 1000  # m³ → L
    P_L_per_s = env.co2_production_rate  # L/s per person
    Q_L_per_s = env.ventilation_rate  # L/s
    C_out = 400.0  # 外界CO₂ ppm
    
    dt_s = dt * 60  # 分钟→秒
    
    for i in range(1, len(t)):
        # CO₂变化率 (ppm/s)
        production = (P_L_per_s * env.num_occupants) / V_L * 1e6
        ventilation = (Q_L_per_s * (co2[i-1] - C_out)) / V_L * 1e6
        
        co2[i] = co2[i-1] + (production - ventilation) * dt_s
        
        # 驾驶员警觉性模型（CO₂影响）
        if co2[i] < 1000:
            co2_effect = 1.0
        elif co2[i] < 2000:
            co2_effect = 1.0 - 0.1 * (co2[i] - 1000) / 1000
        elif co2[i] < 3000:
            co2_effect = 0.9 - 0.15 * (co2[i] - 2000) / 1000
        elif co2[i] < 5000:
            co2_effect = 0.75 - 0.25 * (co2[i] - 3000) / 2000
        else:
            co2_effect = 0.5
        
        # 叠加时间效应（持续驾驶疲劳）
        time_fatigue = max(0, 1.0 - 0.05 * t[i] / 60)
        
        alertness[i] = min(co2_effect, time_fatigue)
    
    return t, co2, alertness


# ==================== 测试场景 ====================
if __name__ == "__main__":
    print("=" * 80)
    print("座舱CO₂浓度仿真 + DMS融合分析")
    print("=" * 80)
    
    scenarios = [
        ("外循环+1人", CabinEnvironment(
            num_occupants=1, ventilation_rate=20)),
        ("内循环+1人", CabinEnvironment(
            num_occupants=1, ventilation_rate=0)),
        ("内循环+4人", CabinEnvironment(
            num_occupants=4, ventilation_rate=0)),
        ("内循环+4人(2小时)", CabinEnvironment(
            num_occupants=4, ventilation_rate=0)),
    ]
    
    for name, env in scenarios:
        duration = 120 if "2小时" in name else 30
        t, co2, alert = simulate_cabin_co2(env, duration)
        
        print(f"\n场景: {name}")
        print(f"  初始CO₂: {co2[0]:.0f} ppm")
        print(f"  最终CO₂: {co2[-1]:.0f} ppm")
        print(f"  峰值CO₂: {np.max(co2):.0f} ppm @ {t[np.argmax(co2)]:.0f}min")
        print(f"  警觉性: {alert[0]:.2f} → {alert[-1]:.2f}")
        print(f"  警觉性下降: {(1-alert[-1]/alert[0])*100:.1f}%")
        
        # DMS误判分析
        if co2[-1] > 2000:
            print(f"  ⚠️ CO₂>{co2[-1]:.0f}ppm: DMS可能误判为疲劳")
            print(f"  建议: 自动切换外循环+开窗通风")
        elif co2[-1] > 1000:
            print(f"  ⚠️ CO₂>{co2[-1]:.0f}ppm: 轻微警觉性下降")
    
    # DMS+CO₂融合策略
    print(f"\n{'='*80}")
    print("DMS + CO₂传感器融合策略")
    print(f"{'='*80}")
    print("""
    1. CO₂ < 1000ppm: DMS正常判定
    2. CO₂ 1000-2000ppm: DMS疲劳判定降权10%
    3. CO₂ 2000-3000ppm: DMS疲劳判定降权25% + 提示通风
    4. CO₂ >3000ppm: DMS判定可能误判 → 强制外循环
    
    融合输出:
    - 实际疲劳 = DMS疲劳 × (1 - CO₂影响因子)
    - CO₂影响因子 = max(0, (CO₂-1000)/4000)
    """)

# 空调联动策略
def auto_ventilation_control(co2_ppm, fatigue_level):
    """
    基于CO₂和疲劳等级的自动空调策略
    """
    if co2_ppm > 3000 or fatigue_level > 0.7:
        return ('fresh_air', 100, 'open_window_prompt')  # 紧急
    elif co2_ppm > 2000 or fatigue_level > 0.5:
        return ('fresh_air', 80, None)  # 切外循环
    elif co2_ppm > 1500:
        return ('fresh_air', 50, None)  # 部分外循环
    else:
        return ('auto', 'auto', None)  # 正常