TS-073111 — Urban intersections are among the highest‑risk environments for automated and human‑driven vehicles due to occlusions, complex right‑of‑way, mixed traffic, and inconsistent connectivity. On‑board perception alone often misses beyond‑line‑of‑sight actors, while centralized or game 

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…

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…