In-vehicle snesors, IMU, and Unsprung Mass vertical velocities measurements dataset from semi-active vehicle

This dataset is made for traditional, machine learning, and deep neural-network-based virtual sensor development and evaluation. There are these data fields: Driver torque requirement, ESP regulation, Master cylinder pressure, Steering angle, Steering angle direction, "Steering angle optimized, Vehicle velocity, Front-Left (FL) wheel velocity, Front-Right(FR) wheel velocity, Rear-Left (RL) wheel velocity, Rear-right (RR) wheel velocity, Acceleration X axis, "Acceleration Y axis, Acceleration Z axis, Body sideslip angle, Roll rate, Longitudinal velocity, Transversal velocity, Yaw rate, FL Unsprung-Mass (UM) vertical velocity, FR UM vertical velocity, RL UM vertical velocity, RR UM vertical velocity. Data was sampled and recorded with 100 Hz rate. UM vertical velocities were estimated from measurements made by physica UM vertical displacement sensors. Data was recorded during special maneuvers on Vehicle Testing Grounds. The tests and data is described in the associated article. The dataset consists of [Train, Validation, Test] parts that has [272, 61, 60] thausa

本数据集旨在服务于传统机器学习及基于深度神经网络的虚拟传感器开发与评估。其中包含以下数据字段：驾驶员扭矩需求、ESP调节、主缸压力、转向角度、转向角度方向、优化后的转向角度、车辆速度、前左（FL）轮速度、前右（FR）轮速度、后左（RL）轮速度、后右（RR）轮速度、X轴加速度、Y轴加速度、Z轴加速度、车身侧滑角、横摆率、纵向速度、横向速度、偏航率、前左（FL）非悬挂质量（UM）垂直速度、前右（FR）UM垂直速度、后左（RL）UM垂直速度、后右（RR）UM垂直速度。数据以100Hz的采样率进行采集和记录。UM垂直速度是通过physica公司UM垂直位移传感器的测量值进行估算的。数据是在车辆测试场地的特定操作中记录的。相关测试和数据在关联的文章中进行了描述。数据集由[训练集、验证集、测试集]三部分组成，分别包含[272、61、60]个样本。