Virtual Vehicle Research GmbH (Austria)
In research, Virtual Vehicle Research GmbH (Austria) stands highest in Physical Sciences (#8,587 of 12,888 worldwide) and Engineering (#5,209 of 6,636 worldwide), 2022–2025. Relative to its size it is most specialised in Automotive Engineering — Automotive Engineering is 28.5× its share of world research.
- World rank, 2022–2025
- #16,904 of 28,054 · #21,135 all time
- Rank in Austria
- #92 of 168
- Research works
- 926 ▼ 25% vs 2013–17
- Citations
- 5.7k 6.2 per fractional work
- Top-10% rate
- 9.7% record average 16.5%
- Open access
- 25% world 28%
What is Virtual Vehicle Research GmbH (Austria) known for in research?
The fields where it stands highest, 2022–2025, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Physical SciencesDomain | #8,587 of 12,888 | 10.0% | 144 | #11811 | |
| EngineeringField | #5,209 of 6,636 | 8.1% | 105 | #5929 |
Each strip is that field’s whole ranked pool, with the notch where Virtual Vehicle Research GmbH (Austria) sits in it, in the colour of the band that rank falls in. The track under the rate is the rate itself: it carries no world mark, because the world rate differs by field (from about 6% to 21% in this record).
What does Virtual Vehicle Research GmbH (Austria) specialise in?
Where its research is concentrated relative to its size: Automotive Engineering takes 28.5× the share of its output that it takes of world research.
- Automotive EngineeringSubfield · 25.6 works29×
Location quotient, a volume reading rather than an impact one. It surfaces small, lopsided specialities.
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Engineering, 4.2×. Every wedge is a field page.
- Engineering 4.2×
- Decision Sciences 2.9×
- Computer Science 2.2×
- Psychology 1.9×
- Chemical Engineering 1.6×
- Physics and Astronomy 0.8×
- Earth and Planetary Sciences 0.6×
- Materials Science 0.4×
- Environmental Science 0.4×
- Business, Management and Accounting 0.4×
- Health Professions 0.2×
- Neuroscience 0.2×
- Social Sciences 0.1×
- Mathematics 0.1×
- Medicine 0.1×
- Economics, Econometrics and Finance 0.1×
- Chemistry 0.0×
- Agricultural and Biological Sciences 0.0×
- Biochemistry, Genetics and Molecular Biology 0.0×
Who are the top researchers at Virtual Vehicle Research GmbH (Austria)?
Ranked on the composite score, Selim Solmaz, Martin Benedikt and Josef Zehetner lead among researchers whose main affiliation is Virtual Vehicle Research GmbH (Austria).
- 1 Selim Solmaz Austria · #519,454 worldwide 62 citations · 22 works
- 2 Martin Benedikt Austria · #777,029 worldwide 31 citations · 24 works
- 3 Josef Zehetner Austria · #806,584 worldwide 33 citations · 26 works
- 4 Michael Stolz Austria · #883,889 worldwide 63 citations · 37 works
- 5 Alexander Stocker Austria · #1,005,684 worldwide 67 citations · 47 works
- 6 Thomas Steidl Austria · #1,015,584 worldwide 0 citations · 16 works
- 7 Anton Fuchs Austria · #1,055,072 worldwide 22 citations · 36 works
- 8 Georg Stettinger Austria · #1,063,878 worldwide 21 citations · 21 works
- 9 Klaus Six Austria · #1,068,948 worldwide 36 citations · 19 works
- 10 Daniel Watzenig Austria · #1,116,034 worldwide 39 citations · 63 works
Which keywords describe research at Virtual Vehicle Research GmbH (Austria)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Autonomous Vehicles, Deep Learning, Collision Avoidance, Sensor Fusion, Driver Assistance Systems, Trajectory Prediction, Electric Vehicles and Driver Behavior.
- Path Planning
- Vehicular Ad Hoc Networks
- DSRC Standards
- Vehicle Dynamics
- SLAM
- 3D Mapping
- Smart Grid
- Mobile Robots
- Metamodeling
- Thermal Management
- Railway Dynamics
- Model Predictive Control
- Driver Distraction
- Trust
- Mental Workload
- High-Speed Trains
- Electric Vehicles
- Driver Assistance Systems
- Collision Avoidance
- Deep Learning
- Autonomous Vehicles
- Machine Learning
- Sensor Fusion
- Trajectory Prediction
- Driver Behavior
- Intelligent Transportation Systems
- Human Factors
- Automation
- Rolling Contact Fatigue
- Ground Vibration
- Control Systems
- Lithium-ion Batteries
- Traffic Flow
- Robotics
- Software Development
- Control Strategies
- Security Analysis
- Battery Management Systems
- Thermal Runaway
- Energy Storage Systems
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 40 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 40 words, with their numbers
- Autonomous Vehicles24▲ 68×4 topics
- Deep Learning23▲ 4.0×23 topics
- Machine Learning15▲ 2.8×12 topics
- Collision Avoidance14▲ 46×3 topics
- Sensor Fusion13▲ 72×3 topics
- Driver Assistance Systems11▲ 119×1 topic
- Trajectory Prediction11▲ 119×1 topic
- Electric Vehicles10▲ 21×4 topics
- Driver Behavior10▲ 78×2 topics
- High-Speed Trains8▲ 75×3 topics
- Intelligent Transportation Systems8▲ 32×3 topics
- Mental Workload8▲ 88×2 topics
- Human Factors7▲ 56×2 topics
- Trust7▲ 15×2 topics
- Automation7▲ 63×1 topic
- Driver Distraction7▲ 112×1 topic
- Rolling Contact Fatigue7▲ 72×2 topics
- Model Predictive Control6▲ 14×4 topics
- Ground Vibration6▲ 137×1 topic
- Railway Dynamics6▲ 137×1 topic
- Control Systems5▲ 17×2 topics
- Thermal Management5▲ 9.0×5 topics
- Lithium-ion Batteries5▲ 6.8×2 topics
- Metamodeling5▲ 111×2 topics
- Traffic Flow4▲ 25×2 topics
- Mobile Robots4▲ 24×2 topics
- Robotics4▲ 9.3×2 topics
- Smart Grid4▲ 6.0×5 topics
- Software Development4▲ 48×2 topics
- 3D Mapping4▲ 32×1 topic
- Control Strategies4▲ 16×3 topics
- SLAM4▲ 32×1 topic
- Security Analysis4▲ 13×2 topics
- Vehicle Dynamics4▲ 38×2 topics
- Battery Management Systems4▲ 14×1 topic
- DSRC Standards4▲ 68×1 topic
- Thermal Runaway4▲ 14×1 topic
- Vehicular Ad Hoc Networks4▲ 68×1 topic
- Energy Storage Systems3▲ 15×2 topics
- Path Planning3▲ 15×3 topics
Which research topics does Virtual Vehicle Research GmbH (Austria) publish most on?
By volume in 2022–2025: Autonomous Vehicle Technology and Safety, Human-Automation Interaction and Safety, Railway Engineering and Dynamics and Robotics and Sensor-Based Localization.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Autonomous Vehicle Technology and Safety Automotive Engineering 11 works
- 2 Human-Automation Interaction and Safety Social Psychology 7 works
- 3 Railway Engineering and Dynamics Mechanical Engineering 6 works
- 4 Robotics and Sensor-Based Localization Aerospace Engineering 4 works
- 5 Advanced Battery Technologies Research Automotive Engineering 4 works
- 6 Vehicular Ad Hoc Networks (VANETs) Electrical and Electronic Engineering 4 works
- 7 Electric and Hybrid Vehicle Technologies Automotive Engineering 3 works
- 8 Traffic and Road Safety Safety, Risk, Reliability and Quality 3 works
- 9 Vehicle Dynamics and Control Systems Automotive Engineering 3 works
- 10 Robotic Path Planning Algorithms Computer Vision and Pattern Recognition 3 works
How open and international is its research?
Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 28% of research is openly available.
World: 19% is written across borders.
How has Virtual Vehicle Research GmbH (Austria)'s research output changed?
Output in 2018–2022 was 25% lower than in 2013–2017.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Other research institutions in Graz
- University of Graz
- Graz University of Technology
- Medical University of Graz
- Universitätsklinik für Frauenheilkunde und Geburtshilfe
- Anstalt für Verbrennungskraftmaschinen List (Austria)
- Joanneum Research
- Graz University Hospital
- Computer Algorithms for Medicine
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.