Identifying relevant traffic situations from simulation data for testing ADAS and fully automated vehicles - A multilayer model concept

Sippl C, Wessner J, German R (2016)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2016

Series: Proceedings

City/Town: Paris, France

Pages Range: 155-163

Conference Proceedings Title: Proceedings of the DSC 20126 Europe VR Driving Simulation Conference & Exhibition, Sept. 7-9

Event location: Paris FR

URI: https://www.driving-simulation.com/site/identifying-relevant-traffic-situations-from-simulation-data-for-testing-adas-and-autonomous-vehicles-a-multilayer-model-concept/

Authors with CRIS profile

Christoph Sippl Computer Science 7 (Computer Networks and Communication Systems) Reinhard German Computer Science 7 (Computer Networks and Communication Systems)

How to cite

APA:

Sippl, C., Wessner, J., & German, R. (2016). Identifying relevant traffic situations from simulation data for testing ADAS and fully automated vehicles - A multilayer model concept. In Proceedings of the DSC 20126 Europe VR Driving Simulation Conference & Exhibition, Sept. 7-9 (pp. 155-163). Paris, FR: Paris, France.

MLA:

Sippl, Christoph, Joseph Wessner, and Reinhard German. "Identifying relevant traffic situations from simulation data for testing ADAS and fully automated vehicles - A multilayer model concept." Proceedings of the DSC 2016 Europe - Driving Simulation and Virtual Reality Conference, Paris Paris, France, 2016. 155-163.

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