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

Citation Author(s):
Eldar Šabanovič (Vilnius Gediminas technical university)
Paulius Kojis (Vilnius Gediminas technical university)
Valentin Ivanov (Vilnius Gediminas technical university)
Miguel Dhaens (Tenneco Automotive Europe)
Viktor Skrickij (Vilnius Gediminas technical university)
Submitted by:
Eldar Sabanovic
Last updated:
DOI:
10.21227/9w6h-bp73
Data Format:
No Ratings Yet

Abstract

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

Instructions:

Data fields names are in the *.mat files in variables XFields and YFields. Training, Validation and Testing input data is in XTrain, XValid, XTest, target data is in YTrain, XValid, XTest. For example in XTrain, each cell holds samples recorded during one test. The cells with same number in XTrain corresponds to ground truth in YTrain, XValid coresponds to YValid, XTest corresponds to YTest.

Funding Agency
European Union Horizon 2020 Framework Program, Marie Skłodowska-Curie actions
Grant Number
872907