There has recently been a wide expansion of hardware to assist in autonomous driving tasks. On this project, we focus on using some state-of-the-art deep learning workloads in connected autonomous vehicle (CAV) scenarios,such as object detection and object tracking to evaluate the heterogeneous hardware.
Computer and Systems Architecture | Controls and Control Theory | Navigation, Guidance, Control, and Dynamics
Ahmad, Mustafa, "Edge Heterogeneous Hardware Evaluation Based on Real Connected and Autonomous Vehicles (CAVs) Workloads" (2019). ROEU 2018-19. 8.