Supplementary Material to: Road profile computation using smartphone-measured acceleration

Data sets consists of data acquired by five smartphones: four serving as acceleration sensors and one controlling device. The master device collects the localization data from global navigation satellite systems (GNSS) and communicates over Bluetooth with the the sensor smartphones. They collect acceleration data at ca 250 Hz. At this stage the sensors (smartphones) were installed to the car body over the front wheels of the vehicle (sensor 1 & 2 over left, sensor 3 & 4 over right wheel). They were aligned along the front car axle as shown in Figure 1 so the z-axis of accelerometer covered the gravity vector. The instrumented vehicle was Alfa Romeo Giulietta. Measurements were repeated seven times with different driving speeds on a route with new asphalt pavement and four rubber speed bump illustrated in Figure 2. The bumps' cross-sections along the road axis were 0.88 m long and 0.06 m high. The registered acceleration signals were used in model calibration and evaluation procedures. The dataset, attached in Acceleration.Signal.csv, consists of six columns: - rideId - individual number of the single ride over four speed bumps, - smartphoneId - individual number of the smartphone mounted in the car, - bumpNo - individual number of the speed bump, - chainage - chainage [m] calculated on the basis of speed measurement and sampling frequancy, - az - raw acceleration signal [m/s2 ], - speed - car speed calculated on the basis of GNNS measurement [km/h ], Data in table is resampled to exact frequency of 250 Hz. Chainage is calculated on the basis of GNSS-acquired speed. Chainage was shifted, so the zero approximately covers the middle of the speed bump. Acknowledgments The authors would like to thank the employees of Heller Consult sp. z o. o. for their work in preparing, conducting, and processing measurements, in particular Arkadiusz Dyczkowki, Emil Łopata, Piotr Pasiński, Andrzej Nadowski, andMarta Mączko. The work was carried out under a programme of, and co-funded by, the European Space Agency. The views expressed in this work are those of the authors and can in no way be taken to reflect the offcial opinion of the European Space Agency.本数据集包含5台智能手机采集的实验数据，其中4台作为加速度传感器，1台作为控制设备。主控设备采集全球导航卫星系统（Global Navigation Satellite Systems，GNSS）的定位数据，并通过蓝牙与作为传感器的智能手机进行通信。所有传感器均以约250Hz的采样频率采集加速度数据。 此时传感器（智能手机）被安装在车辆前轮上方的车身处：传感器1与2安装于左侧前轮上方，传感器3与4安装于右侧前轮上方，并沿汽车前轴对齐，如图1所示，因此加速度计的z轴与重力矢量方向一致。 本次实验的搭载车辆为阿尔法·罗密欧·朱利亚（Alfa Romeo Giulietta）。实验在一条铺有新沥青路面且设有4条橡胶减速带的测试路线上，以不同车速重复开展了7次测量，测试路线如图2所示。该减速带沿道路轴线的横截面尺寸为长0.88m、高0.06m。 所记录的加速度信号被用于模型校准与评估流程。 附于Acceleration.Signal.csv文件中的数据集共包含6列数据： - rideId：单次通过4条减速带的行程唯一编号 - smartphoneId：安装于车辆内的智能手机唯一编号 - bumpNo：减速带的唯一编号 - chainage：基于车速测量与采样频率计算得到的桩号，单位为m - az：原始加速度信号，单位为m/s² - speed：基于GNSS测量计算得到的车辆速度，单位为km/h 表格中的数据已被重采样至250Hz的精确采样频率。桩号基于GNSS获取的车速计算得到，并进行了偏移处理，使零点大致覆盖减速带的中点位置。 致谢 作者谨向Heller Consult sp. z o. o.的全体工作人员致谢，感谢其在测量准备、实施与数据处理过程中付出的工作，特别感谢Arkadiusz Dyczkowki、Emil Łopata、Piotr Pasiński、Andrzej Nadowski以及Marta Mączko。 本研究工作由欧洲空间局（European Space Agency）立项并联合资助。本文所表达的观点仅代表作者本人，绝不代表欧洲空间局的官方立场。