Infrastructure Enabled Autonomy (IEA) is a new paradigm that employs a distributed intelligence architecture for connected autonomous vehicles by offloading core functionalities to the infrastructure. In this paper, we develop a simulation framework that can be used to study the concept. A key challenge for such a simulation is the rapid increase in the scale of the computations with the size of the infrastructure to be considered. Our simulation framework is designed to be distributed and scales proportionally with the infrastructure. By integrally using both the hardware controllers and communication devices as part of the simulation framework, we achieve an optimal balance between modeling of the dynamics and sensors, and reusing real hardware for simulation of proprietary or complex communication methods. Multiple cameras on the infrastructure are simulated. The simulation of the camera image processing is done in distributed hardware and the resultant position information is transmitted wirelessly to the computer simulating the autonomous vehicle. We demonstrate closed loop control of a single vehicle following given waypoints using information from multiple cameras located on Road-Side-Units.
@article{arxiv.1802.01787,
title = {A Distributed Hybrid Hardware-In-the-Loop Simulation framework for Infrastructure Enabled Autonomy},
author = {Abhishek Nayak and Kenny Chour and Tyler Marr and Deepika Ravipati and Sheelabhadra Dey and Alvika Gautam and Swaminathan Gopalswamy and Sivakumar Rathinam},
journal= {arXiv preprint arXiv:1802.01787},
year = {2018}
}