修改了算法代码,并建立了一个简单的训练脚本.修改bert处理二维输入,移除PPO的permute参数

Env/__init__.py

@@ -0,0 +1,15 @@
+"""
+Multi-Agent Scenario Environment
+
+多智能体场景环境
+"""
+
+from .scenario_env import MultiAgentScenarioEnv, PolicyVehicle
+from .simple_idm_policy import ConstantVelocityPolicy
+
+__all__ = [
+    'MultiAgentScenarioEnv',
+    'PolicyVehicle',
+    'ConstantVelocityPolicy',
+]
+

Env/scenario_env.py

@@ -86,6 +86,9 @@ class MultiAgentScenarioEnv(ScenarioEnv):
         if self.engine is None:
             raise ValueError("Broken MetaDrive instance.")
 
+        # 在engine.reset()之前清理对象
+        self.before_reset()
+
         # 记录专家数据中每辆车的位置，接着全部清除，只保留位置等信息，用于后续生成
         _obj_to_clean_this_frame = []
         self.car_birth_info_list = []
@@ -165,10 +168,10 @@ class MultiAgentScenarioEnv(ScenarioEnv):
         self.episode_rewards = defaultdict(float)
         self.episode_lengths = defaultdict(int)
 
-        self.controlled_agents.clear()
-        self.controlled_agent_ids.clear()
-
+        # 调用父类reset会清理场景
         super().reset(seed)  # 初始化场景
+        
+        # 重新生成车辆
         self._spawn_controlled_agents()
 
         return self._get_all_obs()
@@ -298,6 +301,26 @@ class MultiAgentScenarioEnv(ScenarioEnv):
 
                 # ✅ 关键：注册到引擎的 active_agents，才能参与物理更新
                 self.engine.agent_manager.active_agents[agent_id] = vehicle
+    
+    def before_reset(self):
+        """在reset之前清理对象"""
+        # 清理所有可控车辆
+        if hasattr(self, 'controlled_agents') and hasattr(self, 'engine'):
+            # 使用MetaDrive的clear_objects方法清理
+            if hasattr(self.engine, 'clear_objects'):
+                try:
+                    self.engine.clear_objects(list(self.controlled_agents.keys()))
+                except:
+                    pass
+            
+            # 从agent_manager中移除
+            if hasattr(self.engine, 'agent_manager'):
+                for agent_id in list(self.controlled_agents.keys()):
+                    if agent_id in self.engine.agent_manager.active_agents:
+                        self.engine.agent_manager.active_agents.pop(agent_id)
+            
+            self.controlled_agents.clear()
+            self.controlled_agent_ids.clear()
 
     def _get_traffic_light_state(self, vehicle):
         """

Env/simple_idm_policy.py

@@ -6,13 +6,8 @@ class ConstantVelocityPolicy:
 
     def act(self):
         self.step_num += 1
-        if self.step_num % 30 < 15:
-            throttle = 1.0
-        else:
-            throttle = 1.0
-
-        steering = 0.1
-
-        # return [steering, throttle]
-
-        return [0.0,0.05]
+        # 简单的前进策略：直行 + 较大油门
+        steering = 0.0  # 直行
+        throttle = 0.5  # 中等油门，让车辆有明显运动
+        
+        return [steering, throttle]