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- {"sceneNumber": "共测试2个用例", "testMileageSum": "1.07公里", "testDurationSum": "1分29秒", "algorithmComprehensiveScore": 62.46, "algorithmLevel": "一般", "details": {"safe": {"name": "安全性", "weight": "20.0%", "noObjectCar": false, "score": 19.75, "level": "较差", "scoreList": [19.75, 19.75], "levelDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "details": {"safeDistance": {"name": "距离类型", "score": 10.0, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"LatSD": {"name": "LatSD", "average": 40.0, "max": 40.0, "min": 40.0, "rate": "0.0%", "range": "[2, inf)"}}, "builtin": {"LatSD": {"name": "LatSD", "data": [40.0, 40.0], "markLine": ["2"]}}, "custom": {}, "description1": "LatSD指标表现良好，平均值在合理范围内且不存在不合格用例；。", "description2": "经计算可知，LatSD指标位于合理区间的占比为100.0%。"}, "safeAcceleration": {"name": "加速度类型", "score": 5.11, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"DRAC": {"name": "DRAC", "average": 10.0, "max": 10.0, "min": 10.0, "rate": "100.0%", "range": "[0, 5]"}, "BTN": {"name": "BTN", "average": 40.0, "max": 40.0, "min": 40.0, "rate": "100.0%", "range": "[0, 1]"}, "STN": {"name": "STN", "average": 9.53, "max": 9.53, "min": 9.53, "rate": "100.0%", "range": "[0, 1]"}}, "builtin": {"DRAC": {"name": "DRAC", "data": [10.0, 10.0], "markLine": ["5"]}, "BTN": {"name": "BTN", "data": [40.0], "markLine": ["1"]}, "STN": {"name": "STN", "data": [9.53, 9.53], "markLine": ["1"]}}, "custom": {}, "description1": "DRAC、BTN和STN指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。", "description2": "经计算可知，DRAC指标位于合理区间的占比为0.0%，BTN指标位于合理区间的占比为0.0%，STN指标位于合理区间的占比为0.0%。"}, "safeProbability": {"name": "概率类型", "score": 6.1, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"collisionRisk": {"name": "碰撞风险程度", "average": 40.0, "max": 40.0, "min": 40.0, "rate": "100.0%", "range": "[0, 10]"}, "collisionSeverity": {"name": "碰撞严重程度", "average": 40.0, "max": 40.0, "min": 40.0, "rate": "100.0%", "range": "[0, 10]"}}, "builtin": {"collisionRisk": {"name": "碰撞风险程度", "data": [40.0, 40.0], "markLine": ["10"]}, "collisionSeverity": {"name": "碰撞严重程度", "data": [40.0, 40.0], "markLine": ["10"]}}, "custom": {}, "description1": "碰撞风险程度和碰撞严重程度指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。", "description2": "经计算可知，碰撞风险程度指标位于合理区间的占比为0.0%，碰撞严重程度指标位于合理区间的占比为0.0%。"}, "customType": {"name": "自定义x类型", "score": 50.0, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"ldw_miss_warning_count2": {"name": "车道偏离漏预警次数2", "average": 0.0, "max": 0.0, "min": 0.0, "rate": "0.0%", "range": "[0, 1.0]"}}, "builtin": {}, "custom": {"ldw_miss_warning_count2": {"name": "车道偏离漏预警次数2", "data": [0.0, 0.0], "markLine": [1.0]}}, "description1": "车道偏离漏预警次数2指标表现良好，平均值在合理范围内且不存在不合格用例；。", "description2": "经计算可知，车道偏离漏预警次数2指标位于合理区间的占比为100.0%。"}}, "description1": "未满足设计指标要求。其中有2个用例得分低于60分，占比为100.00%，需优化算法在距离类型、加速度类型、概率类型和自定义x类型上的表现；", "description2": "安全性在距离类型、加速度类型、概率类型和自定义x类型上存在严重风险，需要重点优化。"}, "function": {"name": "功能性", "weight": "20.0%", "noObjectCar": false, "score": 46.73, "level": "较差", "scoreList": [46.73, 46.73], "levelDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "details": {"functionACC": {"name": "ACC", "score": 52.73, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"followSpeedDeviation": {"name": "跟车速度偏差", "average": 48.52, "max": 48.52, "min": 48.52, "range": "[0, 2]"}, "followDistanceDeviation": {"name": "跟车距离偏差", "average": 2.86, "max": 2.86, "min": 2.86, "range": "[0, 3]"}, "followStopDistance": {"name": "跟停距离", "average": 34.63, "max": 34.63, "min": 34.63, "range": "[4, inf)"}}, "builtin": {"followSpeedDeviation": {"name": "跟车速度偏差", "data": [48.52, 48.52], "markLine": ["2"]}, "followDistanceDeviation": {"name": "跟车距离偏差", "data": [2.86, 2.86], "markLine": ["3"]}, "followStopDistance": {"name": "跟停距离", "data": [34.63, 34.63], "markLine": ["4"]}}, "custom": {}, "description1": "跟车距离偏差和跟停距离指标表现良好，平均值在合理范围内且不存在不合格用例；\n跟车速度偏差指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。", "description2": "经计算可知，跟车速度偏差指标位于合理区间的占比为0.0%，跟车距离偏差指标位于合理区间的占比为100.0%，跟停距离指标位于合理区间的占比为100.0%。"}, "functionLKA": {"name": "LKA", "score": 49.28, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"ldw_miss_warning_count": {"name": "车道偏离漏预警次数", "average": 9.61, "max": 9.61, "min": 9.61, "range": "[0, 1.0]"}, "laneDistance": {"name": "与近侧车道线的横向距离", "average": 0.01, "max": 0.01, "min": 0.01, "range": "[1.1, inf)"}, "centerDistanceExpectation": {"name": "车道中心线横向距离分布期望", "average": 0.12, "max": 0.12, "min": 0.12, "range": "[0, 0.15]"}, "centerDistanceStandardDeviation": {"name": "车道中心线横向距离分布标准差", "average": 0.15, "max": 0.15, "min": 0.15, "range": "[0, 0.2]"}, "centerDistanceMax": {"name": "车道中心线横向距离分布最大值", "average": 0.74, "max": 0.74, "min": 0.74, "range": "[0, 0.5]"}, "centerDistanceMin": {"name": "车道中心线横向距离分布最小值", "average": 0.0, "max": 0.0, "min": 0.0, "range": "[0, 0.5]"}, "centerDistanceFrequency": {"name": "横向相对位置震荡频率", "average": 0.57, "max": 0.57, "min": 0.57, "range": "[0, 0.1]"}, "centerDistanceRange": {"name": "横向相对位置震荡极差", "average": 0.64, "max": 0.64, "min": 0.64, "range": "[0, 0.7]"}}, "builtin": {"laneDistance": {"name": "与近侧车道线的横向距离", "data": [0.01, 0.01], "markLine": ["1.1"]}, "centerDistanceExpectation": {"name": "车道中心线横向距离分布期望", "data": [0.12, 0.12], "markLine": ["0.15"]}, "centerDistanceStandardDeviation": {"name": "车道中心线横向距离分布标准差", "data": [0.15, 0.15], "markLine": ["0.2"]}, "centerDistanceMax": {"name": "车道中心线横向距离分布最大值", "data": [0.74, 0.74], "markLine": ["0.5"]}, "centerDistanceMin": {"name": "车道中心线横向距离分布最小值", "data": [0.0, 0.0], "markLine": ["0.5"]}, "centerDistanceFrequency": {"name": "横向相对位置震荡频率", "data": [0.57, 0.57], "markLine": ["0.1"]}, "centerDistanceRange": {"name": "横向相对位置震荡极差", "data": [0.64, 0.64], "markLine": ["0.7"]}}, "custom": {"ldw_miss_warning_count": {"name": "车道偏离漏预警次数", "data": [9.61, 9.61], "markLine": [1.0]}}, "description1": "车道中心线横向距离分布期望、车道中心线横向距离分布标准差、车道中心线横向距离分布最小值和横向相对位置震荡极差指标表现良好，平均值在合理范围内且不存在不合格用例；\n车道偏离漏预警次数、与近侧车道线的横向距离、车道中心线横向距离分布最大值和横向相对位置震荡频率指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。", "description2": "经计算可知，车道偏离漏预警次数指标位于合理区间的占比为0.0%，与近侧车道线的横向距离指标位于合理区间的占比为0.0%，车道中心线横向距离分布期望指标位于合理区间的占比为100.0%，车道中心线横向距离分布标准差指标位于合理区间的占比为100.0%，车道中心线横向距离分布最大值指标位于合理区间的占比为0.0%，车道中心线横向距离分布最小值指标位于合理区间的占比为100.0%，横向相对位置震荡频率指标位于合理区间的占比为0.0%，横向相对位置震荡极差指标位于合理区间的占比为100.0%。"}, "functionLDW": {"name": "LDW", "score": 10.0, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"ldw_miss_warning_count3": {"name": "车道偏离漏预警次数3", "average": 9.61, "max": 9.61, "min": 9.61, "range": "[0, 1.0]"}}, "builtin": {}, "custom": {"ldw_miss_warning_count3": {"name": "车道偏离漏预警次数3", "data": [9.61, 9.61], "markLine": [1.0]}}, "description1": "车道偏离漏预警次数3指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。", "description2": "经计算可知，车道偏离漏预警次数3指标位于合理区间的占比为0.0%。"}}, "description1": "未满足设计指标要求。其中有2个用例得分低于60分，占比为100.00%，需优化算法在ACC、LKA和LDW上的表现；", "description2": "算法在ACC、LKA和LDW功能上需要重点优化。"}, "compliance": {"name": "合规性", "weight": "20.0%", "score": 100.0, "level": "优秀", "scoreList": [100, 100], "levelDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "details": {"deduct1": {"name": "轻微违规（扣1分）", "score": 100.0, "level": "优秀", "indexes": {"overspeed10": {"name": "超速10%以下", "times": 0}, "overspeed10_20": {"name": "超速10%-20%", "times": 0}}}, "deduct3": {"name": "中等违规（扣3分）", "score": 100.0, "level": "优秀", "indexes": {"pressSolidLine": {"name": "压实线", "times": 0}}}, "deduct6": {"name": "危险违规（扣6分）", "score": 100.0, "level": "优秀", "indexes": {"runRedLight": {"name": "闯红灯", "times": 0}, "overspeed20_50": {"name": "超速20%-50%", "times": 0}}}, "deduct12": {"name": "重大违规（扣12分）", "score": 100.0, "level": "优秀", "indexes": {"overspeed50": {"name": "超速50%以上", "times": 0}}}}, "description1": "车辆在本轮测试中无违反交通法规行为；", "description2": "共有2个用例，其中0个用例出现违规行为。"}, "comfort": {"name": "舒适性", "weight": "10.0%", "score": 91.66, "level": "优秀", "scoreList": [91.66, 91.66], "levelDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "details": {"comfortLat": {"name": "横向舒适性", "score": 93.33, "level": "优秀", "gradeDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "indexes": {"zigzag": {"name": "画龙", "avgScore": 33.33, "maxScore": 33.33, "minScore": 33.33, "avgNumber": "1.00", "avgDuration": "3.40", "avgStrength": "0.00"}, "shake": {"name": "晃动", "avgScore": 100.0, "maxScore": 100.0, "minScore": 100.0, "avgNumber": "0.00", "avgDuration": "0.00", "avgStrength": "0.00"}}, "builtin": {"zigzag": {"name": "画龙", "data": [33.33, 33.33]}, "shake": {"name": "晃动", "data": [100.0, 100.0]}}, "custom": {}, "description1": "晃动指标最低分超过设计指标要求，算法在2个用例中均表现良好；\n画龙指标平均分超过设计指标要求，但是算法存在2个表现不佳用例，需要改进算法在这些用例中的表现；。", "description2": "经计算可知，算法在画龙指标上表现良好的概率为0.0%，在晃动指标上表现良好的概率为100.0%。"}, "comfortLon": {"name": "纵向舒适性", "score": 90.0, "level": "优秀", "gradeDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "indexes": {"cadence": {"name": "顿挫", "avgScore": 100.0, "maxScore": 100.0, "minScore": 100.0, "avgNumber": "0.00", "avgDuration": "0.00", "avgStrength": "0.00"}, "slamAccelerate": {"name": "急加速", "avgScore": 100.0, "maxScore": 100.0, "minScore": 100.0, "avgNumber": "0.00", "avgDuration": "0.00", "avgStrength": "0.00"}}, "builtin": {"cadence": {"name": "顿挫", "data": [100.0, 100.0]}, "slamAccelerate": {"name": "急加速", "data": [100.0, 100.0]}}, "custom": {}, "description1": "顿挫和急加速指标最低分超过设计指标要求，算法在2个用例中均表现良好；。", "description2": "经计算可知，算法在顿挫指标上表现良好的概率为100.0%，在急加速指标上表现良好的概率为100.0%。"}}, "description1": "乘客在本轮测试中体验舒适；", "description2": "算法在舒适性维度上的表现满足设计指标要求"}, "efficient": {"name": "高效性", "weight": "20.0%", "score": 50.0, "level": "较差", "scoreList": [50, 50], "levelDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "details": {"efficientDrive": {"name": "行驶", "score": 0.0, "level": "较差", "gradeDistribution": {"优秀": 0, "良好": 0, "一般": 0, "较差": 100}, "indexes": {"averageSpeed": {"name": "平均速度", "average": 42.97, "max": 42.97, "min": 42.97, "number": 2, "range": "[0.0, 30.0]"}}, "builtin": {"averageSpeed": {"name": "平均速度", "data": [42.97, 42.97], "markLine": ["30"]}}, "custom": {}, "description1": "平均速度指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。"}, "efficientStop": {"name": "停车", "score": 100.0, "level": "优秀", "gradeDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "indexes": {"stopDuration": {"name": "停车时长", "average": 0.0, "max": 0.0, "min": 0.0, "number": 0, "range": "[0, 5]"}}, "builtin": {"stopDuration": {"name": "停车时长", "data": [0.0, 0.0], "markLine": ["5"]}}, "custom": {}, "description1": "停车时长指标表现良好，平均值在合理范围内且不存在不合格用例；。"}}, "description1": "未满足设计指标要求。其中有2个用例得分低于60分，占比为100.00%，需优化算法在averageSpeed上的表现；", "description2": "算法应该优化车辆的规划控制逻辑，提高算法的通行效率。"}, "customTest": {"name": "自定义x维度", "weight": "10.0%", "score": 100.0, "level": "优秀", "scoreList": [100, 100], "levelDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "details": {"customType": {"name": "自定义x类型", "score": 100.0, "level": "优秀", "gradeDistribution": {"优秀": 100, "良好": 0, "一般": 0, "较差": 0}, "indexes": {"ldw_miss_warning_count4": {"name": "车道偏离漏预警次数4", "average": 9.61, "max": 9.61, "min": 9.61, "range": "[0, 1.0]"}, "ldw_miss_warning_count2": {"name": "车道偏离漏预警次数2", "average": 9.61, "max": 9.61, "min": 9.61, "range": "[0, 1.0]"}}, "builtin": {}, "custom": {"ldw_miss_warning_count4": {"name": "车道偏离漏预警次数4", "data": [9.61, 9.61], "markLine": [1.0]}, "ldw_miss_warning_count2": {"name": "车道偏离漏预警次数2", "data": [9.61, 9.61], "markLine": [1.0]}}, "description1": "车道偏离漏预警次数4和车道偏离漏预警次数2指标平均值在合理范围外，算法在大部分用例下均表现不佳，需重点优化。"}}, "description1": "算法在本轮测试中的表现优秀；", "description2": "算法在自定义x维度维度上的表现满足设计指标要求。"}}, "algorithmResultDescription": "综上所述，建议算法优化在安全性、功能性和高效性指标上的表现。"}
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