To plan safe and comfortable trajectories for automated vehicles on highways, accurate predictions of traffic situations are needed.
Already today, driver assistance systems help to make daily traffic more comfortable and safer.
To overcome these challenges, an extended environment model is a reasonable choice.
More precisely, we investigate how a state-of-the-art approach for lateral motion prediction is influenced by one selected external condition, namely the traffic density.
By observing their environment as well as other traffic participants, humans are enabled to drive road vehicles safely.