@inproceedings {pub3645pub3723,
	title = {Analysis of a Speech-Based Intersection Assistant in Real Urban Traffic},
	author = {Dennis Orth AND Nico Andreas Steinhardt AND Bram Bolder AND Mark Dunn AND Dorothea Kolossa AND Martin Ernst Heckmann},
	year = {2018},
	month = {November},
	abstract = {We have recently proposed a speech-based on-demand intersection assistant, which supports the driver at urban intersections. It provides information on  the current traffic situation on the right-hand side and recommends suitable gaps in the traffic. This system has previously assumed a more or less constant flow of the traffic. To also handle situations of more dynamic urban traffic, including vehicles that may be slowing down or stopping, we have now extended our previous approach by a dynamic vehicle model. This model predicts the future traffic vehicle state based on second-order vehicle dynamics.
We perform an in depth analysis of our system on a set of recordings under various traffic conditions. In this analysis we compare in particular the previous and the novel vehicle model.
Both approaches lead to a correct recommendation in approximately 90\% of the cases. Unexpectedly, the dynamic model does not lead to significant improvements in the system behavior, despite its increased accuracy.},
	publisher = {IEEE},
	booktitle = {The 21st IEEE International Conference on Intelligent Transportation Systems}
}