Ghaith Ale

• Lane-Level Localization Research: Developing a high-precision vehicle positioning framework that accurately locates a vehicle within a specific lane despite degraded or noisy GPS signals. • Geometric Spatial Mapping: Segmenting road surface markings and applying camera intrinsics alongside flat-ground assumptions to project 2D pixel coordinates into precise 3D ground-plane distances.

• Automated Driver Assessment: Programmed temporal rule engines to evaluate driver traffic behaviors, specifically tracking lane-change execution safety, head-pose mirror checks, indicator usage cycles, and active compliance with traffic lights and regulatory road signs. • Behavioral Compliance Fusion: Synchronized real-time Traffic Sign Recognition (TSR) and multi-state Traffic Light Classification models with time-series CAN-bus vehicle telemetry and HD-map spatial priors to grade traffic rule adherence.