更新代码，解决合并的数据中缺少laneOffset信号的问题

core/processors/built_in/lst.py

@@ -1047,6 +1047,7 @@ class FinalDataProcessor:
                 print(f"Error: Required input file not found: {obj_state_path}")
                 return False
             # 处理交通灯数据并保存
+
             df_traffic = self._process_trafficlight_data()
             if not df_traffic.empty:
                 traffic_csv_path = self.output_dir / "Traffic.csv"
@@ -1054,7 +1055,23 @@ class FinalDataProcessor:
                 print(f"Successfully created traffic light data file: {traffic_csv_path}")
             # Load and process data
             df_object = pd.read_csv(obj_state_path, dtype={"simTime": float}, low_memory=False)
-
+            df_ego = df_object[df_object["playerId"] == 1]
+            points = df_ego[["posX", "posY"]].values
+            window_size = 4
+            fitting_instance = PolynomialCurvatureFitting(lane_map_path)
+            result_list = fitting_instance.fit_and_project(points, window_size)
+
+            curvHor_values = [result["curvHor"] for result in result_list]
+            curvature_change_value = [result["curvHorDot"] for result in result_list]
+            min_distance = [result["laneOffset"] for result in result_list]
+
+            indices = df_object[df_object["playerId"] == 1].index
+            if len(indices) == len(curvHor_values):
+                df_object.loc[indices, "curvHor"] = curvHor_values
+                df_object.loc[indices, "curvHorDot"] = curvature_change_value
+                df_object.loc[indices, "laneOffset"] = min_distance
+            else:
+                print("计算值的长度与 playerId == 1 的行数不匹配！")
             # Process and merge data
             df_merged = self._merge_optional_data(df_object)