Automotive CAN bus data: An Example Dataset from the AEGIS Big Data Project

Here you find an example research data dataset for the automotive demonstrator within the "AEGIS - Advanced Big Data Value Chain for Public Safety and Personal Security" big data project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732189. The time series data has been collected during trips conducted by three drivers driving the same vehicle in Austria. The dataset contains 20Hz sampled CAN bus data from a passenger vehicle, e.g. WheelSpeed FL (speed of the front left wheel), SteerAngle (steering wheel angle), Role, Pitch, and accelerometer values per direction. GPS data from the vehicle (see signals 'Latitude_Vehicle' and 'Longitude_Vehicle' in h5 group 'Math') and GPS data from the IMU device (see signals 'Latitude_IMU', 'Longitude_IMU' and 'Time_IMU' in h5 group 'Math') are included. However, as it had to be exported with single-precision, we lost some precision for those GPS values. For data analysis we use R and R Studio (https://www.rstudio.com/) and the library h5. e.g. check file with R code: library(h5) f <- h5file("file path/20181113_Driver1_Trip1.hdf") summary(f["CAN/Yawrate1"][,]) summary(f["Math/Latitude_IMU"][,]) h5close(f)