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Quantifying Road Grade Based on In-Vehicle Measurements with Global Positioning System Receivers

机译:基于全球定位系统接收器的车载测量量化道路坡度

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Variability in real-world vehicle fuel use and emissions during a trip depends primarily onvehicle speed, acceleration, and road grade. However, there is not a standard method formeasuring road grade from a moving vehicle. Changes in road grade of more than a percentagepoint significantly affect fuel use and emission rates. Consumer grade Global PositioningSystem receivers with barometric altimeter (GPS/BA) are used to measure position andelevation. Data were collected from 12 vehicles, each using 3 GPS receivers, for a total of 36repeated GPS/BA runs on eight one-way routes in the Research Triangle Park, NC region. Roadgrade was estimated by combining data from 9, 18, and 36 runs and applying linear regression tonon-overlapping and adjacent road segments of length Δd. The accuracy of the estimated roadgrade was evaluated based on comparison to estimates from aircraft-based LIDARmeasurements. The average grade is found to be accurate. The average precision is 0.39, 0.25,and 0.16 percentage points, for sample sizes of 9, 18, and 36 runs, respectively, among 1,116individual road segments. The proportion of segments that have road grade precision within atarget of ±0.5 percentage points are 80 percent for 9 runs, 98 percent for 18 runs, and 99.8percent for 36 runs. Thus, the use of a low cost GPS/BA is a promising approach for accurateand precise measurement of grade relative to data quality needs for quantifying variability in fueluse and emissions.
机译:旅途中实际车辆燃料使用和排放的变化主要取决于 车辆速度,加速度和道路坡度。但是,没有标准的方法可用于 从行驶中的车辆测量道路坡度。道路坡度变化超过百分之一 点会严重影响燃料的使用和排放率。消费级全球定位 带气压高度计(GPS / BA)的系统接收器用于测量位置和 海拔。从12辆汽车中收集数据,每辆汽车使用3个GPS接收器,总共36辆 重复的GPS / BA在北卡罗莱纳州研究三角公园的8条单向路线上运行。路 通过合并9、18和36次运行的数据并将线性回归应用于 长度为Δd的非重叠和相邻道路段。估算道路的准确性 基于与基于机载激光雷达的估计值的比较,对等级进行了评估 测量。发现平均成绩是准确的。平均精度为0.39、0.25, 1,116个样本的样本量分别为9,116和0.16个百分点 个别路段。路段内具有道路坡度精度的路段的比例 ±0.5个百分点的目标是9次运行为80%,18次运行为98%和99.8 36次跑步的百分比。因此,使用低成本的GPS / BA是一种有希望的精确定位方法 相对于数据质量需求的等级的精确测量,以量化燃料的变异性 使用和排放。

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