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

<p>Here you find an example research data dataset for the automotive demonstrator within the &quot;AEGIS -&nbsp; Advanced Big Data Value Chain for Public Safety and Personal Security&quot; big data project, which has received funding from the European Union&rsquo;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.</p> <p>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.</p> <p>GPS data from the vehicle (see signals &#39;Latitude_Vehicle&#39; and &#39;Longitude_Vehicle&#39; in h5 group &#39;Math&#39;) and GPS data from the IMU device (see signals &#39;Latitude_IMU&#39;, &#39;Longitude_IMU&#39; and &#39;Time_IMU&#39; in h5 group &#39;Math&#39;) are included. However, as it had to be exported with single-precision, we lost some precision for those GPS values.</p> <p>&nbsp;</p> <p>For data analysis we use R and R Studio (https://www.rstudio.com/) and the library h5.</p> <p>e.g. check file with R code:</p> <p>library(h5)</p> <p>f &lt;- h5file(&quot;file path/20181113_Driver1_Trip1.hdf&quot;)</p> <p>summary(f[&quot;CAN/Yawrate1&quot;][,])</p> <p>summary(f[&quot;Math/Latitude_IMU&quot;][,])</p> <p>h5close(f)</p>