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Environment perception and event detection for object prediction in traffic Sonka, Adrian ; Liesner, Louisa ; Pawellek, Torben ; Krauns, Florian ; Henze, Roman ; Küçükay, Ferit

By: Contributor(s): Publication details: Göteborg Chalmers University of Technology. SAFER Vehicle and Traffic Safety Centre, 2015Description: s. 79-83Subject(s): Online resources: In: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents: September 9-11, 2015 Gothenburg, Sweden: proceedingsNotes: Konferens: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents, 2015, Gothenburg Abstract: Information about the vehicle environment becomes increasingly important as the development of automated driving functions progresses. This paper not only addresses a perception of the current environment, but also an estimation of possible future states. A multi-purpose method for measuring objects, lane markings and road boundaries using a reference sensor system that includes laserscanners is presented. The focus lies on recording a comprehensive environment description that is needed for the examination of vehicle interaction. The results are utilized in the correspondent tool chain for postprocessing, event detection and analysis for object prediction applications. In a final step, different possible applications are introduced.
Item type: Reports, conferences, monographs
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Konferens: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents, 2015, Gothenburg

Information about the vehicle environment becomes increasingly important as the development of automated driving functions progresses. This paper not only addresses a perception of the current environment, but also an estimation of possible future states. A multi-purpose method for measuring objects, lane markings and road boundaries using a reference sensor system that includes laserscanners is presented. The focus lies on recording a comprehensive environment description that is needed for the examination of vehicle interaction. The results are utilized in the correspondent tool chain for postprocessing, event detection and analysis for object prediction applications. In a final step, different possible applications are introduced.