Available Technologies
# of Displayed Technologies: 7 / 7
Applied Category Filter (Click To Remove): Autonomous Components & Smart/Connected Mobility
AI-Driven Intersection Safety System for Vulnerable Road User Protection
TS-070954 — The Need
Intersections are among the most dangerous areas on U.S. roadways, accounting for approximately 25% of traffic fatalities and nearly half of all injuries annually. Vulnerable Road Users (VRUs), including pedestrians and cyclists, face increasing risk due to complex traffic dynamics and limi…
- College: College of Engineering (COE)
- Inventors: Yurtsever, Ekim; Giuliani, Michele; Rizzoni, Giorgio
- Licensing Officer: Ashouripashaki, Mandana
Predictive V2X Torque Control for Multi-E-Axle EV Efficiency
TS-070632 — The Need
As electric vehicles (EVs) evolve toward multi-e-axle architectures, traditional energy management strategies fall short in optimizing power distribution and minimizing energy waste. Current systems lack the predictive intelligence to adapt to dynamic driving conditions, leading to suboptim…
- College: College of Engineering (COE)
- Inventors: Safder, Ahmad Hussain; Ahmed, Qadeer; Hanif, Athar
- Licensing Officer: Ashouripashaki, Mandana
Sustainability-Aware Management of Autonomous Mobile Robot (AMR) Fleets
TS-068477 — The Need
Autonomous Mobile Robots (AMRs) are critical to modern, highly automated environments, operating 24/7 to optimize tasks, increase throughput, and meet demanding operational requirements. However, most task allocation and charging solutions focus solely on maximizing performance metrics like…
- College: College of Engineering (COE)
- Inventors: Brocanelli, Marco
- Licensing Officer: Randhawa, Davinder
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: Giles, David
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
