Year: 2023
Type: conference-paper
Abstract: In this paper, we present an autonomous vehicles (AV) research testbed with photo-realistic visualisation and simulation capability.Compared to Oak Ridge National Labs CAVE system, Microsoft's AirSim, and MATLAB's Vehicle Dynamics Blockset approach, the key difference is a decoupled and modular system architecture which allows developers to focus on only one aspect of the whole system and be productive with minimal training.Basically, the proposed system has a game engine, an external hardware accelerator for vehicle dynamical models, and a GPU equipped computer to run the AI algorithms.Our vision is to have all vehicle dynamical models to be built in MATLAB/Simulink and run on a hardware accelerator like Speedgoat, which is a leading software and hardware framework for scientific system modelling and hardware in the loop simulation.The proposed photo realistic visualization environment is Unreal Engine based, and all AI models are keras based.This decoupled system architecture allows all vehicle dynamical models and AI decision making to be implemented outside the Unreal Engine, while the game engine doing all collision detections and reporting.Similarly, all traffic and pedestrian movement stochastic models can be implemented outside the game engine, allowing a framework agnostic approach to be used throughout the whole system.
Authors: Alexandra Dubs, Victoria Correa Andrade, Mark Ellis, Seth Ganley, Bayazit Karaman, ONUR TOKER
Institution: Florida Polytechnic University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Awards: MRI: CNS: Acquisition of Real-Time Hardware-in-the-Loop Simulation for Verification of Connected and Autonomous Vehicles, Research Initiation Award: Microwave Synthesis of Imidazole Compounds to Investigate Allosteric Binding to VCP, Excellence in Research: Yakubovsky Calculations for Six-Nucleon Bound States, G884219770
OpenAlex ID: W4377966992