@mastersthesis {pub4988,
	title = {Fast Classification of Driving Behavior Possibilities for Improved Trajectory Prediction},
	author = {Daniela Aguirre Salazar},
	year = {2021},
	abstract = {A fundamental part of the optimal performance of advanced driver assistance systems (ADAS) functions, such as trajectory planners, is to quickly classify other vehicles{\textquoteright}  possible behavior. One way to approach this, assuming that both kinematic data from the other vehicles and road information are available, is to use traffic models to perform simulations of vehicle trajectories under the possible interaction scenarios between agents and, after comparing them with the actual trajectory using similarity measures, perform probability inference.

The emphasis of this thesis is the selection of the appropriate similarity measure to compare the trajectories. Twelve different similarity measures were used, necessary transformations based on certain parameters were performed to have a fair comparison. The parameters for the transformations were chosen and tuned using data from positional and velocity experiments. This would allow to intrinsically carry a classifier component, that would be adjusted through said parameter and would modify the sensitivity in relation to positional and velocity changes. In addition, several performance and robustness experiments were performed to compare all measures and conclude which is more appropriate for the application of predicted and actual trajectory comparison. To demonstrate that using similarity measures as a basis for deducing probabilities is suitable for the application, an example of a simple probability inference is given and it is also shown how this connects to the development of the classifier.

In the end, a summary of the experiments{\textquoteright} analyses is given, and the conclusions obtained from them. Recommendations for future work are also given, referring to the state-of-the-art work related to calculating possible behaviors among the traffic agents.},
	publisher = {University of Kassel},
	booktitle = {University of Kassel}
}