diff --git a/pytest.ini b/pytest.ini
new file mode 100644
index 0000000..442bb94
--- /dev/null
+++ b/pytest.ini
@@ -0,0 +1,3 @@
+[pytest]
+pythonpath = src
+testpaths = tests
diff --git a/requirements_pc.txt b/requirements_pc.txt
index 506720a..89bfd92 100644
--- a/requirements_pc.txt
+++ b/requirements_pc.txt
@@ -3,3 +3,4 @@
 pyzmq==27.1.0
 numpy==2.4.3
 python-dotenv==1.2.2
+pytest==9.0.2
diff --git a/src/common/json_utils.py b/src/common/json_utils.py
index 62e214a..0ce705a 100644
--- a/src/common/json_utils.py
+++ b/src/common/json_utils.py
@@ -34,7 +34,7 @@
         path: 書き込み先の JSON ファイルのパス
         data: 書き込むデータ
     """
-    path.parent.mkdir(exist_ok=True)
+    path.parent.mkdir(parents=True, exist_ok=True)
     with open(path, "w", encoding="utf-8") as f:
         json.dump(
             data, f, ensure_ascii=False, indent=2,
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/tests/__init__.py
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..5d06702
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,44 @@
+"""テスト共通フィクスチャ"""
+
+import numpy as np
+import pytest
+
+from common import config
+
+
+@pytest.fixture()
+def straight_line_image() -> np.ndarray:
+    """中央に暗い縦線があるグレースケール画像"""
+    h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+    img = np.full((h, w), 200, dtype=np.uint8)
+    cx = w // 2
+    img[:, cx - 1 : cx + 2] = 30
+    return img
+
+
+@pytest.fixture()
+def blank_image() -> np.ndarray:
+    """線のない均一なグレースケール画像"""
+    h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+    return np.full((h, w), 180, dtype=np.uint8)
+
+
+@pytest.fixture()
+def binary_with_hole() -> np.ndarray:
+    """中央に穴がある二値画像（クロージングテスト用）"""
+    h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+    binary = np.zeros((h, w), dtype=np.uint8)
+    binary[3:h - 3, w // 2 - 2 : w // 2 + 3] = 255
+    # 中央に 2px の穴をあける
+    binary[h // 2 : h // 2 + 2, :] = 0
+    return binary
+
+
+@pytest.fixture()
+def binary_line() -> np.ndarray:
+    """中央に太い白線がある二値画像"""
+    h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+    binary = np.zeros((h, w), dtype=np.uint8)
+    cx = w // 2
+    binary[:, cx - 3 : cx + 4] = 255
+    return binary
diff --git a/tests/test_fitting.py b/tests/test_fitting.py
new file mode 100644
index 0000000..5791fbf
--- /dev/null
+++ b/tests/test_fitting.py
@@ -0,0 +1,147 @@
+"""fitting モジュールのテスト"""
+
+import numpy as np
+import pytest
+
+from pc.vision.fitting import (
+    MIN_FIT_ROWS,
+    clean_and_fit,
+    ransac_polyfit,
+    theil_sen_fit,
+)
+
+
+class TestTheilSenFit:
+    """theil_sen_fit のテスト"""
+
+    def test_linear_data(self) -> None:
+        """直線データから正しい slope と intercept を復元できる"""
+        y = np.arange(10, dtype=float)
+        # x = 2.0 * y + 5.0
+        x = 2.0 * y + 5.0
+        slope, intercept = theil_sen_fit(y, x)
+        assert slope == pytest.approx(2.0, abs=1e-6)
+        assert intercept == pytest.approx(5.0, abs=1e-6)
+
+    def test_with_outlier(self) -> None:
+        """外れ値が1つあっても正しい傾きを推定できる"""
+        y = np.arange(11, dtype=float)
+        x = 1.0 * y + 3.0
+        # 1点を大きく外す
+        x[5] = 100.0
+        slope, intercept = theil_sen_fit(y, x)
+        assert slope == pytest.approx(1.0, abs=0.2)
+        assert intercept == pytest.approx(3.0, abs=1.0)
+
+    def test_two_points(self) -> None:
+        """2点でも傾きを計算できる"""
+        y = np.array([0.0, 10.0])
+        x = np.array([5.0, 15.0])
+        slope, intercept = theil_sen_fit(y, x)
+        assert slope == pytest.approx(1.0, abs=1e-6)
+        assert intercept == pytest.approx(5.0, abs=1e-6)
+
+    def test_single_point(self) -> None:
+        """1点しかない場合は slope=0, intercept=median(x)"""
+        y = np.array([5.0])
+        x = np.array([10.0])
+        slope, intercept = theil_sen_fit(y, x)
+        assert slope == 0.0
+        assert intercept == pytest.approx(10.0)
+
+    def test_horizontal_line(self) -> None:
+        """水平な線（slope=0）を正しく推定できる"""
+        y = np.arange(10, dtype=float)
+        x = np.full(10, 7.0)
+        slope, intercept = theil_sen_fit(y, x)
+        assert slope == pytest.approx(0.0, abs=1e-6)
+        assert intercept == pytest.approx(7.0, abs=1e-6)
+
+
+class TestRansacPolyfit:
+    """ransac_polyfit のテスト"""
+
+    def test_clean_quadratic(self) -> None:
+        """ノイズなしの2次曲線を正しくフィットできる"""
+        ys = np.arange(20, dtype=float)
+        # x = 0.1 * y^2 - 2.0 * y + 10.0
+        xs = 0.1 * ys**2 - 2.0 * ys + 10.0
+        coeffs = ransac_polyfit(ys, xs, 2, 50, 5.0)
+        assert coeffs is not None
+        assert coeffs[0] == pytest.approx(0.1, abs=0.01)
+        assert coeffs[1] == pytest.approx(-2.0, abs=0.1)
+
+    def test_with_outliers(self) -> None:
+        """30% の外れ値があっても正しくフィットできる"""
+        rng = np.random.default_rng(42)
+        ys = np.arange(30, dtype=float)
+        xs = 0.05 * ys**2 + 3.0
+        # 30% を大きく外す
+        outlier_idx = rng.choice(30, 9, replace=False)
+        xs[outlier_idx] += rng.uniform(50, 100, 9)
+        coeffs = ransac_polyfit(ys, xs, 2, 100, 5.0)
+        assert coeffs is not None
+        assert coeffs[0] == pytest.approx(0.05, abs=0.02)
+
+    def test_too_few_points(self) -> None:
+        """点が不足している場合は None を返す"""
+        ys = np.array([1.0, 2.0])
+        xs = np.array([3.0, 4.0])
+        assert ransac_polyfit(ys, xs, 2, 50, 5.0) is None
+
+
+class TestCleanAndFit:
+    """clean_and_fit のテスト"""
+
+    def test_basic_fit(self) -> None:
+        """正常なデータでフィッティングできる"""
+        ys = np.arange(15, dtype=float)
+        xs = 0.5 * ys + 10.0
+        coeffs = clean_and_fit(
+            ys, xs,
+            median_ksize=0,
+            neighbor_thresh=0.0,
+        )
+        assert coeffs is not None
+        # 2次の係数はほぼ 0，1次はほぼ 0.5
+        assert coeffs[-2] == pytest.approx(0.5, abs=0.1)
+
+    def test_too_few_points(self) -> None:
+        """MIN_FIT_ROWS 未満のデータは None を返す"""
+        n = MIN_FIT_ROWS - 1
+        ys = np.arange(n, dtype=float)
+        xs = np.arange(n, dtype=float)
+        assert clean_and_fit(
+            ys, xs, median_ksize=0, neighbor_thresh=0.0,
+        ) is None
+
+    def test_neighbor_filter_removes_outlier(self) -> None:
+        """近傍フィルタが外れ値を除去できる"""
+        ys = np.arange(20, dtype=float)
+        xs = np.full(20, 15.0)
+        xs[10] = 100.0  # 大きな外れ値
+        coeffs = clean_and_fit(
+            ys, xs,
+            median_ksize=0,
+            neighbor_thresh=5.0,
+        )
+        assert coeffs is not None
+        # 外れ値除去後，x ≈ 15.0 の直線になる
+        poly = np.poly1d(coeffs)
+        assert poly(10) == pytest.approx(15.0, abs=2.0)
+
+    def test_residual_removal(self) -> None:
+        """残差除去が外れ値を取り除ける"""
+        ys = np.arange(20, dtype=float)
+        xs = 1.0 * ys + 5.0
+        xs[3] = 80.0
+        xs[17] = -50.0
+        coeffs = clean_and_fit(
+            ys, xs,
+            median_ksize=0,
+            neighbor_thresh=0.0,
+            residual_thresh=10.0,
+        )
+        assert coeffs is not None
+        poly = np.poly1d(coeffs)
+        assert poly(10) == pytest.approx(15.0, abs=3.0)
diff --git a/tests/test_json_utils.py b/tests/test_json_utils.py
new file mode 100644
index 0000000..03020fc
--- /dev/null
+++ b/tests/test_json_utils.py
@@ -0,0 +1,47 @@
+"""json_utils モジュールのテスト"""
+
+from pathlib import Path
+
+from common.json_utils import read_json, write_json
+
+
+class TestWriteReadRoundtrip:
+    """write_json / read_json の往復テスト"""
+
+    def test_dict_roundtrip(self, tmp_path: Path) -> None:
+        """dict を書き込んで読み込むと一致する"""
+        path = tmp_path / "test.json"
+        data = {"key": "value", "number": 42}
+        write_json(path, data)
+        assert read_json(path) == data
+
+    def test_list_roundtrip(self, tmp_path: Path) -> None:
+        """list を書き込んで読み込むと一致する"""
+        path = tmp_path / "test.json"
+        data = [{"a": 1}, {"b": 2}]
+        write_json(path, data)
+        assert read_json(path) == data
+
+    def test_creates_parent_dir(
+        self, tmp_path: Path,
+    ) -> None:
+        """親ディレクトリが存在しなくても自動作成される"""
+        path = tmp_path / "sub" / "dir" / "test.json"
+        data = {"created": True}
+        write_json(path, data)
+        assert path.exists()
+        assert read_json(path) == data
+
+    def test_japanese_text(self, tmp_path: Path) -> None:
+        """日本語テキストが正しく保存・復元される"""
+        path = tmp_path / "test.json"
+        data = {"title": "テスト", "memo": "日本語メモ"}
+        write_json(path, data)
+        assert read_json(path) == data
+
+    def test_overwrite(self, tmp_path: Path) -> None:
+        """既存ファイルを上書きできる"""
+        path = tmp_path / "test.json"
+        write_json(path, {"v": 1})
+        write_json(path, {"v": 2})
+        assert read_json(path) == {"v": 2}
diff --git a/tests/test_line_detector.py b/tests/test_line_detector.py
new file mode 100644
index 0000000..ce186c7
--- /dev/null
+++ b/tests/test_line_detector.py
@@ -0,0 +1,204 @@
+"""line_detector モジュールのテスト"""
+
+import numpy as np
+import pytest
+
+from common import config
+from pc.vision.line_detector import (
+    ImageParams,
+    LineDetectResult,
+    build_result,
+    detect_line,
+    fit_row_centers,
+    no_detection,
+)
+
+
+class TestNoDetection:
+    """no_detection のテスト"""
+
+    def test_returns_not_detected(
+        self, blank_image: np.ndarray,
+    ) -> None:
+        """detected=False で全フィールドがデフォルト値"""
+        result = no_detection(blank_image)
+        assert result.detected is False
+        assert result.position_error == 0.0
+        assert result.heading == 0.0
+        assert result.curvature == 0.0
+        assert result.poly_coeffs is None
+        assert result.row_centers is None
+        assert result.binary_image is not None
+
+
+class TestBuildResult:
+    """build_result のテスト"""
+
+    def test_straight_center_line(self) -> None:
+        """画像中央の直線は position_error ≈ 0"""
+        h = config.FRAME_HEIGHT
+        w = config.FRAME_WIDTH
+        center_x = w / 2.0
+        # x = center_x (定数) → coeffs = [0, 0, center_x]
+        coeffs = np.array([0.0, 0.0, center_x])
+        binary = np.zeros((h, w), dtype=np.uint8)
+        result = build_result(coeffs, binary)
+        assert result.detected is True
+        assert result.position_error == pytest.approx(
+            0.0, abs=0.01,
+        )
+        assert result.heading == pytest.approx(
+            0.0, abs=0.01,
+        )
+        assert result.curvature == pytest.approx(
+            0.0, abs=0.01,
+        )
+
+    def test_offset_line(self) -> None:
+        """左にオフセットした直線は position_error > 0"""
+        h = config.FRAME_HEIGHT
+        w = config.FRAME_WIDTH
+        # 左寄りの直線
+        offset_x = w / 4.0
+        coeffs = np.array([0.0, 0.0, offset_x])
+        binary = np.zeros((h, w), dtype=np.uint8)
+        result = build_result(coeffs, binary)
+        assert result.position_error > 0  # 中心より左
+
+
+class TestDetectLine:
+    """detect_line のテスト"""
+
+    def test_current_detects_straight_line(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """現行手法で中央の直線を検出できる"""
+        # 小さいテスト画像用にパラメータを調整
+        params = ImageParams(
+            method="current",
+            clahe_grid=2, blur_size=3,
+            open_size=1, close_width=3,
+            close_height=1,
+        )
+        result = detect_line(
+            straight_line_image, params,
+        )
+        assert result.detected is True
+        assert abs(result.position_error) < 0.5
+
+    def test_current_no_line(
+        self, blank_image: np.ndarray,
+    ) -> None:
+        """均一画像では線を検出しない"""
+        params = ImageParams(method="current")
+        result = detect_line(blank_image, params)
+        assert result.detected is False
+
+    def test_blackhat_detects_straight_line(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """案A で中央の直線を検出できる"""
+        params = ImageParams(
+            method="blackhat",
+            blackhat_ksize=15,
+            binary_thresh=30,
+            blur_size=3,
+            iso_close_size=1,
+            dist_thresh=0.0,
+            min_line_width=1,
+            median_ksize=0,
+            neighbor_thresh=0.0,
+            residual_thresh=0.0,
+        )
+        result = detect_line(
+            straight_line_image, params,
+        )
+        assert result.detected is True
+
+    def test_dual_norm_detects_straight_line(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """案B で中央の直線を検出できる"""
+        params = ImageParams(
+            method="dual_norm",
+            bg_blur_ksize=21,
+            adaptive_block=11, adaptive_c=5,
+            iso_close_size=1,
+            dist_thresh=0.0,
+            min_line_width=1,
+            median_ksize=0,
+            neighbor_thresh=0.0,
+            residual_thresh=0.0,
+        )
+        result = detect_line(
+            straight_line_image, params,
+        )
+        assert result.detected is True
+
+    def test_robust_detects_straight_line(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """案C で中央の直線を検出できる"""
+        params = ImageParams(
+            method="robust",
+            blackhat_ksize=15,
+            adaptive_block=11, adaptive_c=5,
+            iso_close_size=1,
+            dist_thresh=0.0,
+            min_line_width=1,
+            median_ksize=0,
+            neighbor_thresh=0.0,
+            residual_thresh=0.0,
+        )
+        result = detect_line(
+            straight_line_image, params,
+        )
+        assert result.detected is True
+
+    def test_valley_detects_straight_line(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """案D で中央の直線を検出できる"""
+        params = ImageParams(method="valley")
+        result = detect_line(
+            straight_line_image, params,
+        )
+        assert result.detected is True
+
+    def test_default_params(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """params=None でもデフォルトで動作する"""
+        result = detect_line(straight_line_image)
+        assert isinstance(result, LineDetectResult)
+
+    def test_result_has_binary_image(
+        self, straight_line_image: np.ndarray,
+    ) -> None:
+        """結果に二値化画像が含まれる"""
+        result = detect_line(straight_line_image)
+        assert result.binary_image is not None
+        assert result.binary_image.shape == (
+            config.FRAME_HEIGHT, config.FRAME_WIDTH,
+        )
+
+
+class TestFitRowCenters:
+    """fit_row_centers のテスト"""
+
+    def test_detects_binary_line(
+        self, binary_line: np.ndarray,
+    ) -> None:
+        """二値画像の白線から中心をフィッティングできる"""
+        result = fit_row_centers(
+            binary_line, min_width=1,
+        )
+        assert result.detected is True
+        assert abs(result.position_error) < 0.3
+
+    def test_empty_binary(self) -> None:
+        """白ピクセルがない二値画像では検出しない"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        empty = np.zeros((h, w), dtype=np.uint8)
+        result = fit_row_centers(empty, min_width=1)
+        assert result.detected is False
diff --git a/tests/test_morphology.py b/tests/test_morphology.py
new file mode 100644
index 0000000..1cff783
--- /dev/null
+++ b/tests/test_morphology.py
@@ -0,0 +1,142 @@
+"""morphology モジュールのテスト"""
+
+import numpy as np
+import pytest
+
+from common import config
+from pc.vision.morphology import (
+    apply_dist_mask,
+    apply_iso_closing,
+    apply_staged_closing,
+    apply_width_filter,
+)
+
+
+class TestApplyIsoClosing:
+    """apply_iso_closing のテスト"""
+
+    def test_fills_small_hole(
+        self, binary_with_hole: np.ndarray,
+    ) -> None:
+        """小さい穴をクロージングで埋められる"""
+        result = apply_iso_closing(binary_with_hole, 5)
+        h = config.FRAME_HEIGHT
+        w = config.FRAME_WIDTH
+        # 穴があった中央付近が白になっている
+        assert result[h // 2, w // 2] == 255
+
+    def test_small_size_noop(self) -> None:
+        """size < 3 の場合は何もしない"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        binary[5, 5] = 255
+        result = apply_iso_closing(binary, 1)
+        assert np.array_equal(result, binary)
+
+    def test_preserves_shape(
+        self, binary_with_hole: np.ndarray,
+    ) -> None:
+        """出力画像のサイズが入力と同じ"""
+        result = apply_iso_closing(binary_with_hole, 7)
+        assert result.shape == binary_with_hole.shape
+
+
+class TestApplyStagedClosing:
+    """apply_staged_closing のテスト"""
+
+    def test_removes_small_regions(self) -> None:
+        """min_area で小さい領域を除去できる"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        # 大きな領域
+        binary[2:h - 2, w // 2 - 3 : w // 2 + 4] = 255
+        # 小さな孤立点
+        binary[0, 0] = 255
+        result = apply_staged_closing(
+            binary, small_size=3, min_area=5,
+            large_size=0,
+        )
+        assert result[0, 0] == 0  # 孤立点が除去されている
+        assert result[h // 2, w // 2] == 255  # 大領域は残る
+
+    def test_no_min_area(self) -> None:
+        """min_area=0 なら孤立除去をスキップする"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        binary[0, 0] = 255
+        result = apply_staged_closing(
+            binary, small_size=1, min_area=0,
+            large_size=0,
+        )
+        assert result[0, 0] == 255
+
+
+class TestApplyWidthFilter:
+    """apply_width_filter のテスト"""
+
+    def test_keeps_narrow_line(self) -> None:
+        """期待幅以内の線は残す"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        cx = w // 2
+        binary[:, cx - 1 : cx + 2] = 255  # 幅 3
+        result = apply_width_filter(
+            binary, width_near=10, width_far=5,
+            tolerance=2.0,
+        )
+        # 幅 3 は期待幅内なので残る
+        assert np.any(result[h // 2] > 0)
+
+    def test_removes_wide_row(self) -> None:
+        """期待幅を超える行を除去する"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        # 下端に幅いっぱいの白（幅=w）
+        binary[h - 1, :] = 255
+        result = apply_width_filter(
+            binary, width_near=3, width_far=2,
+            tolerance=1.5,
+        )
+        # 幅 w >> 3*1.5 なので除去される
+        assert np.all(result[h - 1] == 0)
+
+    def test_empty_rows_unchanged(self) -> None:
+        """白ピクセルがない行はそのまま"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        result = apply_width_filter(
+            binary, width_near=5, width_far=3,
+            tolerance=2.0,
+        )
+        assert np.array_equal(result, binary)
+
+
+class TestApplyDistMask:
+    """apply_dist_mask のテスト"""
+
+    def test_keeps_center_of_thick_line(self) -> None:
+        """太い線の中心部を残す"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        cx = w // 2
+        binary[:, cx - 5 : cx + 6] = 255  # 幅 11
+        result = apply_dist_mask(binary, thresh=2.0)
+        # 中心は残る
+        assert result[h // 2, cx] > 0
+
+    def test_thresh_zero_noop(self) -> None:
+        """thresh <= 0 の場合は何もしない"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        binary[5, 5] = 255
+        result = apply_dist_mask(binary, thresh=0.0)
+        assert np.array_equal(result, binary)
+
+    def test_removes_thin_line(self) -> None:
+        """細い線（幅1px）は距離変換で除去される"""
+        h, w = config.FRAME_HEIGHT, config.FRAME_WIDTH
+        binary = np.zeros((h, w), dtype=np.uint8)
+        binary[:, w // 2] = 255  # 幅 1px
+        result = apply_dist_mask(binary, thresh=1.0)
+        # 幅 1px の距離変換最大値は 1.0 未満
+        assert np.all(result == 0)
diff --git a/tests/test_params.py b/tests/test_params.py
new file mode 100644
index 0000000..d7bf6fa
--- /dev/null
+++ b/tests/test_params.py
@@ -0,0 +1,145 @@
+"""auto_params / param_store モジュールのテスト"""
+
+from pathlib import Path
+from unittest.mock import patch
+
+import pytest
+
+from pc.steering.pd_control import PdParams
+from pc.vision.line_detector import ImageParams
+
+
+class TestAutoParams:
+    """auto_params の保存・読み込みテスト"""
+
+    @pytest.fixture(autouse=True)
+    def _use_tmp_dir(self, tmp_path: Path) -> None:
+        """PARAMS_DIR を一時ディレクトリに差し替える"""
+        with patch(
+            "pc.steering.auto_params.PARAMS_DIR",
+            tmp_path,
+        ):
+            with patch(
+                "pc.steering.auto_params._CONTROL_FILE",
+                tmp_path / "control.json",
+            ):
+                yield
+
+    def test_save_load_control_roundtrip(self) -> None:
+        """PD パラメータと手法を保存→読込で復元できる"""
+        from pc.steering.auto_params import (
+            load_control,
+            save_control,
+        )
+        params = PdParams(
+            kp=1.0, kh=0.5, kd=0.2,
+            max_steer_rate=0.05,
+            max_throttle=0.6, speed_k=0.4,
+        )
+        save_control(params, "blackhat")
+        loaded, method = load_control()
+        assert method == "blackhat"
+        assert loaded.kp == pytest.approx(1.0)
+        assert loaded.kh == pytest.approx(0.5)
+        assert loaded.max_throttle == pytest.approx(0.6)
+
+    def test_load_control_missing_file(self) -> None:
+        """ファイルがない場合はデフォルト値を返す"""
+        from pc.steering.auto_params import load_control
+        params, method = load_control()
+        assert method == "current"
+        assert params.kp == PdParams().kp
+
+    def test_save_load_detect_params(
+        self, tmp_path: Path,
+    ) -> None:
+        """検出パラメータを手法別に保存→復元できる"""
+        from pc.steering.auto_params import (
+            load_detect_params,
+            save_detect_params,
+        )
+        ip = ImageParams(
+            method="dual_norm",
+            adaptive_block=31,
+            adaptive_c=15,
+        )
+        save_detect_params("dual_norm", ip)
+        loaded = load_detect_params("dual_norm")
+        assert loaded.method == "dual_norm"
+        assert loaded.adaptive_block == 31
+        assert loaded.adaptive_c == 15
+
+    def test_load_detect_unknown_method(self) -> None:
+        """未知の手法は指定手法のデフォルト値を返す"""
+        from pc.steering.auto_params import (
+            load_detect_params,
+        )
+        loaded = load_detect_params("unknown")
+        assert loaded.method == "unknown"
+
+
+class TestParamStore:
+    """param_store の保存・読み込みテスト"""
+
+    @pytest.fixture(autouse=True)
+    def _use_tmp_dir(self, tmp_path: Path) -> None:
+        """プリセットファイルを一時ディレクトリに差し替える"""
+        with patch(
+            "pc.steering.param_store._PD_FILE",
+            tmp_path / "presets_pd.json",
+        ):
+            with patch(
+                "pc.steering.param_store._IMAGE_FILE",
+                tmp_path / "presets_image.json",
+            ):
+                yield
+
+    def test_pd_preset_add_load_delete(self) -> None:
+        """PD プリセットの追加・読込・削除"""
+        from pc.steering.param_store import (
+            PdPreset,
+            add_pd_preset,
+            delete_pd_preset,
+            load_pd_presets,
+        )
+        # 追加
+        preset = PdPreset(
+            title="テスト",
+            memo="メモ",
+            params=PdParams(kp=2.0),
+        )
+        add_pd_preset(preset)
+        presets = load_pd_presets()
+        assert len(presets) == 1
+        assert presets[0].title == "テスト"
+        assert presets[0].params.kp == pytest.approx(2.0)
+
+        # 削除
+        delete_pd_preset(0)
+        assert len(load_pd_presets()) == 0
+
+    def test_image_preset_add_load(self) -> None:
+        """画像処理プリセットの追加・読込"""
+        from pc.steering.param_store import (
+            ImagePreset,
+            add_image_preset,
+            load_image_presets,
+        )
+        ip = ImageParams(
+            method="blackhat", blackhat_ksize=51,
+        )
+        add_image_preset(ImagePreset(
+            title="BH51", memo="テスト", image_params=ip,
+        ))
+        presets = load_image_presets()
+        assert len(presets) == 1
+        assert presets[0].image_params.blackhat_ksize == 51
+
+    def test_load_empty(self) -> None:
+        """ファイルがない場合は空リストを返す"""
+        from pc.steering.param_store import (
+            load_image_presets,
+            load_pd_presets,
+        )
+        assert load_pd_presets() == []
+        assert load_image_presets() == []