Visual Computing

University of Konstanz
2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC)

Traffic visualization in helmet-mounted displays in synchronization with navigation displays

F. Eisenkeil, J. Ernst, R. Stadelhofer, U. Kühne, O. Deussen


One of the major challenges for helicopter pilots are low level flights and landings in degraded visual environments. Without proper assistance systems, the pilots are prone to lose their situational awareness when fog, heavy precipitation, limited sunlight and stirred-up sand or snow degrades their view. In recent years, various synthetic and enhanced vision systems were developed so as to assist the pilots in these demanding situations. We enhance the existing systems by proposing a concept for the visualization of traffic information in head-mounted displays. The intuitive representation provides additional cues about the environment and decreases the pilots’ workload, especially during flights in offshore windparks or while search and rescue operations with many other vehicles operating within a small range.


  author     = {F. Eisenkeil and J. Ernst and R. Stadelhofer and U. Kühne and O. Deussen},
  booktitle  = {2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC)},
  doi        = {10.1109/DASC.2015.7311388},
  issn       = {2155-7195},
  keywords   = {aerospace computing;air traffic;aircraft displays;aircraft navigation;computer vision;data visualisation;helicopters;helmet mounted displays;synchronisation;degraded visual environments;enhanced vision systems;helicopter pilots;helmet-mounted displays;navigation displays;offshore windparks;search and rescue operations;situational awareness;synchronization;synthetic vision systems;traffic information visualization;Air traffic control;Data visualization;Helicopters;Surveillance;Vehicles;Visualization},
  month      = {sep},
  pages      = {3A1-1-3A1-15},
  title      = {Traffic visualization in helmet-mounted displays in synchronization with navigation displays},
  year       = {2015},

Supplemental Material

Paper (.pdf, 2.9 MB)