修改合并数据时地图信息中红绿灯位置缺失，以及HMI，rosbag数据时间戳合并精度问题

core/processors/built_in/lst.py

@@ -567,7 +567,9 @@ class ZipCSVProcessor:
         # df_vehicle.dropna(subset=[col for col in required_pos if col in df_vehicle.columns], inplace=True)
 
         try:
-            df_vehicle["simTime"] = np.round(np.linspace(df_raw["simTime"].tolist()[0], df_raw["simTime"].tolist()[0] + 0.01*(len(df_vehicle)), len(df_vehicle)), 2)
+            # x = np.arange(df_raw["simTime"].tolist()[0], df_raw["simTime"].tolist()[0] + 0.01 * (len(df_vehicle)),0.01)
+            # y = f"{x: .02f}"
+            df_vehicle["simTime"] = np.round(np.linspace(df_raw["simTime"].tolist()[0]+28800, df_raw["simTime"].tolist()[0]+28800 + 0.01*(len(df_vehicle)), len(df_vehicle)), 2)
             df_vehicle["simFrame"] = np.arange(1, len(df_vehicle) + 1)
             df_vehicle["playerId"] = int(player_id)
             df_vehicle['playerId'] = pd.to_numeric(df_vehicle['playerId']).astype(int)
@@ -1019,6 +1021,11 @@ class FinalDataProcessor:
         self.config = config
         self.output_dir = config.output_dir
 
+    def find_closet_idx(self, time, df) -> int:
+        series = (df['simTime'] - time).abs()
+        index = (df['simTime'] - time).abs().idxmin()
+        return (df['simTime'] - time).abs().idxmin()
+
     def process(self) -> bool:
         """执行最终数据合并和处理步骤。"""
         print("--- Starting Final Data Processing ---")
@@ -1074,14 +1081,23 @@ class FinalDataProcessor:
                 df_merged.sort_values(['simTime', 'playerId'], inplace=True)
 
                 # 使用 merge_asof 进行就近合并，不包括 simFrame
-                df_merged = pd.merge_asof(
+                # df_merged = pd.merge_asof(
+                #     df_merged,
+                #     df_ego,
+                #     on='simTime',
+                #     by='playerId',
+                #     direction='nearest',
+                #     tolerance=0.01  # 10ms tolerance
+                # )
+                df_merged = pd.merge(
                     df_merged,
                     df_ego,
-                    on='simTime',
-                    by='playerId',
-                    direction='nearest',
-                    tolerance=0.01  # 10ms tolerance
+                    on=["simTime", "playerId"],
+                    how="left",
+                    suffixes=("", "_map"),
                 )
+                if {"posX_map", "posY_map", "posH_map"}.issubset(df_merged.columns):
+                    df_merged.drop(columns=["posX_map", "posY_map", "posH_map"], inplace=True)
                 print("EgoMap data merged.")
             except Exception as e:
                 print(f"Warning: Could not merge EgoMap data from {egomap_path}: {e}")
@@ -1097,14 +1113,14 @@ class FinalDataProcessor:
 
                 if 'simTime' in df_function.columns:
                     df_function['simTime'] = df_function['simTime'].round(2)
-                    df_function['time'] = df_function['simTime'].round(1).astype(float)
-                    df_merged['time'] = df_merged['simTime'].round(1).astype(float)
-
-                    common_cols = list(set(df_merged.columns) & set(df_function.columns) - {'time'})
+                    df_function['time1'] = df_function['simTime'].apply(lambda x: self.find_closet_idx(x, df_merged))
+                    common_cols = list(set(df_merged.columns) & set(df_function.columns))
                     df_function.drop(columns=common_cols, inplace=True, errors='ignore')
+                    df_merged = df_merged.merge(df_function, right_on='time1', left_index=True, how='left')
+
 
-                    df_merged = pd.merge(df_merged, df_function, on=["time"], how="left")
-                    df_merged.drop(columns=['time'], inplace=True)
+                    df_merged.drop(columns=['time1'], inplace=True)
+                    df_merged.reset_index(drop=True, inplace=True)
                     print("Function data merged.")
                 else:
                     print("Warning: 'simTime' column not found in Function.csv. Cannot merge.")
@@ -1122,20 +1138,18 @@ class FinalDataProcessor:
                 if 'simFrame' in df_obu.columns:
                     df_obu = df_obu.drop(columns=['simFrame'])
 
-                df_obu['time'] = df_obu['simTime'].round(1).astype(float)
-                df_merged['time'] = df_merged['simTime'].round(1).astype(float)
-
-                common_cols = list(set(df_merged.columns) & set(df_obu.columns) - {'time'})
+                df_obu['time2'] = df_obu['simTime'].apply(lambda x: self.find_closet_idx(x, df_merged))
+                common_cols = list(set(df_merged.columns) & set(df_obu.columns))
                 df_obu.drop(columns=common_cols, inplace=True, errors='ignore')
+                df_merged = df_merged.merge(df_obu, right_on = 'time2', left_index=True, how = 'left')
 
-                df_merged = pd.merge(df_merged, df_obu, on=["time"], how="left")
-                df_merged.drop(columns=['time'], inplace=True)
+                df_merged.drop(columns=['time2'], inplace=True)
                 print("OBU data merged.")
             except Exception as e:
                 print(f"Warning: Could not merge OBU data from {obu_path}: {e}")
         else:
             print("OBU data not found or empty, skipping merge.")
-
+        df_merged[['speedH', 'accelX', 'accelY']] = -df_merged[['speedH', 'accelX', 'accelY']]
         return df_merged
 
     def _process_trafficlight_data(self) -> pd.DataFrame:

run.py

@@ -35,8 +35,9 @@ def parse_arguments():
     parser.add_argument(
         '--zip-path',
         type=Path,
-        # default=Path('/home/server/桌面/XGJ/dataprocess/V2V_CSAE53-2020_ForwardCollision_LST_02-01.zip'),
-        default=Path('/home/server/桌面/XGJ/dataprocess/V2I_CSAE53-2020_HazardousLocationW_LST_02-01.zip'),
+        default=Path('/home/server/桌面/XGJ/dataprocess/data_0421/V2V_CSAE53-2020_ForwardCollisionW_LST_01-01.zip'),
+        # default=Path('/home/server/桌面/XGJ/dataprocess/data_0421/V2I_CSAE53-2020_LeftTurnAssist_LST_01-04.zip'),
+        # default=Path('/home/server/桌面/XGJ/dataprocess/data_0421/V2I_CSAE53-2020_LeftTurnAssist_LST_01-01.zip'),
         help='输入的ZIP数据文件路径'
     )