Predicting traffic senarios from LIDAR data set The goal of this project is to develop a clustering algorithm that produces time segments in the data corresponding to different driving scenarios. The scope of the project by only considering a small subset of the data provided by Volvo Cars. The data considered are the object data and the object attributes.
The purpose of this project is to assist the development of the data simulation algorithm, focusing on clustering driving data collected in Gothenburg and separating it into different traffic scenarios. The data is collected as time series using a Velodyne LiDAR sensor. This creates a 360 degree three-dimensional point-cloud at a sampling frequency of 10 Hz.