# of Displayed Technologies: 6 / 6

Applied Category Filter (Click To Remove): Autonomous Components & Smart/Connected Mobility


Vulnerability and Attackability analysis of automotive controllers using structural model of the system
TS-063239 — The Ohio State University has developed a vulnerability analysis technique for connected and autonomous vehicles that assesses the vulnerability and attackability of the automotive controllers to determine the security of the system. The Need Automated vehicle technologies improve safety, assis…
  • College: College of Engineering (COE)
  • Inventors: Renganathan, Vishnu; Ahmed, Qadeer
  • Licensing Officer: Ashouripashaki, Mandana

Novel Deep Learning Model for Reconnaissance of Infrastructure on Drones
TS-063007 — The Need In disaster-stricken areas, timely and accurate reconnaissance is paramount for effective response and recovery efforts. Traditional methods of assessing damage to critical infrastructure, such as power distribution poles, often involve time-consuming manual inspections, leading to delays …
  • College: College of Engineering (COE)
  • Inventors: Shafieezadeh, Abdollah; Bagheri Jeddi, Ashkan
  • Licensing Officer: Mess, David

Surrogates for Concrete Dividers
TS-062834 — Road departure can be extremely dangerous for vehicles. Some vehicles are equipped with road departure mitigation systems to prevent this from happening. However, testing these systems can be difficult and costly, as it involves crashing vehicles into roadside objects. The concrete divider surr…
  • College: College of Engineering (COE)
  • Inventors: Chen, Chi-Chih; Chen, Yaobin; Chien, Stanley; Lin, Jun; Sherony, Rini; Yi, Qiang
  • Licensing Officer: Zinn, Ryan

Surrogates for Metal Guardrails
Road departures remain a significant source of traffic accidents. Tools for limiting road departures are needed to reduce accidents and improve safe driving conditions. The Ohio State University researcher Dr. Chi-Chih Chen, along with a team of researchers, has developed a novel metal guardrai…
  • College: College of Engineering (COE)
  • Inventors: Chen, Chi-Chih; Chen, Yaobin; Chien, Stanley; Lin, Jun; Sherony, Rini
  • Licensing Officer: Zinn, Ryan

Method for real-time estimation of aeroelastic flutter using the parametric flutter margin
TS-062490 — An exemplary parametric flutter margin method and associated system that can be used to identify the structural dynamic characteristics of an Unmanned Aerial Vehicle’s wing in a series of Ground Vibration Tests (GVTs) and initial flight-testing study.
The Need In the aerospace industry, ensuring the safety and certification of aircraft is of paramount importance. One critical challenge faced during the certification process is aeroelastic flutter, an unstable phenomenon that can lead to catastrophic consequences. Conventional flight-testing meth…
  • College: College of Engineering (COE)
  • Inventors: McCrink, Matthew
  • Licensing Officer: Randhawa, Davinder

Vehicle-in-Virtual-Environment Method for Autonomous Driving System Development and Evaluation
TS-054005 — This technology is a Vehicle-in-Virtual Environment (VVE) method for testing and evaluating Autonomous Vehicles (AV). The VVE approach is a safe, reliable, repetitive, and scalable method of testing AVs, decreasing the risks and costs of testing AVs on public roads.
The demand for autonomous vehicles continues to grow as companies and cities realize the effect on the costs, safety, and efficiency that AVs have on everyday lives. Initiatives such as MCity in Detroit, Michigan, and Smart City in Columbus, Ohio, show a strong commitment to the development of aut…
  • College: College of Engineering (COE)
  • Inventors: Guvenc, Levent; Aksun Guvenc, Bilin
  • Licensing Officer: Randhawa, Davinder

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