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