Identifying Relevant Traffic Situations Based on Human Decision Making

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Sippl C, Bock F, Huber B, Djanatliev A, German R
Publisher: Springer Verlag
Publication year: 2019
Conference Proceedings Title: 19. Internationales Stuttgarter Symposium: Automobil- und Motorentechnik
Language: English


FAU Authors / FAU Editors

Bock, Florian
Computer Science 7 (Computer Networks and Communication Systems)
Djanatliev, Anatoli Dr.-Ing.
Computer Science 7 (Computer Networks and Communication Systems)
German, Reinhard Prof. Dr.
Computer Science 7 (Computer Networks and Communication Systems)
Huber, Bernd
Computer Science 7 (Computer Networks and Communication Systems)
Sippl, Christoph
Computer Science 7 (Computer Networks and Communication Systems)


Additional Organisation
Computer Science 7 (Computer Networks and Communication Systems)


Research Fields

Connected Mobility
Computer Science 7 (Computer Networks and Communication Systems)
Informations- und Kommunikationstechnik
Research focus area of a faculty: Technische Fakultät


How to cite

APA:
Sippl, C., Bock, F., Huber, B., Djanatliev, A., & German, R. (2019). Identifying Relevant Traffic Situations Based on Human Decision Making. In 19. Internationales Stuttgarter Symposium: Automobil- und Motorentechnik. Haus der Wirtschaft, Willi-Bleicher-Straße 19, 70174 Stuttgart, Deutschland, DE: Springer Verlag.

MLA:
Sippl, Christoph, et al. "Identifying Relevant Traffic Situations Based on Human Decision Making." Proceedings of the 19. Internationales Stuttgarter Symposium Automobil- und Motorentechnik, Haus der Wirtschaft, Willi-Bleicher-Straße 19, 70174 Stuttgart, Deutschland Springer Verlag, 2019.

BibTeX: 

Last updated on 2019-29-04 at 10:38