优化车辆生成位置偏差问题，新增红绿灯信息采集方法

Env/run_multiagent_env_visual.py

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+from scenario_env import MultiAgentScenarioEnv
+from simple_idm_policy import ConstantVelocityPolicy
+from metadrive.engine.asset_loader import AssetLoader
+import time
+
+WAYMO_DATA_DIR = r"/home/huangfukk/MAGAIL4AutoDrive/Env"
+
+def main():
+    """带可视化的版本（低FPS，约15帧）"""
+    env = MultiAgentScenarioEnv(
+        config={
+            "data_directory": AssetLoader.file_path(WAYMO_DATA_DIR, "exp_converted", unix_style=False),
+            "is_multi_agent": True,
+            "num_controlled_agents": 3,
+            "horizon": 300,
+            
+            # 可视化设置（牺牲性能）
+            "use_render": True,
+            "manual_control": False,
+            
+            "sequential_seed": True,
+            "reactive_traffic": True,
+        },
+        agent2policy=ConstantVelocityPolicy(target_speed=50)
+    )
+
+    obs = env.reset(0)
+    
+    start_time = time.time()
+    total_steps = 0
+    
+    for step in range(10000):
+        actions = {
+            aid: env.controlled_agents[aid].policy.act()
+            for aid in env.controlled_agents
+        }
+
+        obs, rewards, dones, infos = env.step(actions)
+        env.render(mode="topdown")  # 实时渲染
+        
+        total_steps += 1
+        
+        if step % 100 == 0 and step > 0:
+            elapsed = time.time() - start_time
+            fps = total_steps / elapsed
+            print(f"Step {step}: FPS = {fps:.2f}, 车辆数 = {len(env.controlled_agents)}")
+
+        if dones["__all__"]:
+            break
+
+    elapsed = time.time() - start_time
+    fps = total_steps / elapsed
+    print(f"\n总计: {total_steps} 步，耗时 {elapsed:.2f}s，平均FPS = {fps:.2f}")
+    
+    env.close()
+
+
+if __name__ == "__main__":
+    main()
+