To enhance the lane graph construction in the toolbox for better capturing semantic information and its impact on agent behavior, several improvements can be implemented. Firstly, the lane graph construction process could be refined to include more detailed information about lane boundaries, road markings, and traffic signs. This could involve extracting additional features from Lanelet files, such as lane curvature, lane type, and traffic signal locations, to create a more comprehensive representation of the environment.
Secondly, the toolbox could incorporate algorithms for dynamic lane graph updates based on real-time changes in the environment. This would enable the model to adapt to evolving traffic conditions and make more accurate predictions by considering the latest semantic information from the scene.
Additionally, the lane graph visualization capabilities of the toolbox could be enhanced to provide interactive and intuitive displays of the semantic map. This could include features like interactive zooming, highlighting of critical traffic elements, and overlaying predicted trajectories on the lane graph for better contextual understanding. By improving the lane graph construction and visualization functionalities, the toolbox can better capture the semantic context of the environment and its influence on agent behavior.