AVstack: An Open-Source, Reconfigurable Platform for Autonomous Vehicle Development

TL;DR

AVstack is an open-source, flexible platform that facilitates autonomous vehicle development, testing, and analysis, addressing validation challenges and enabling advanced evaluations like vehicle-to-infrastructure and multi-agent collaboration.

Contribution

It introduces AVstack, a reconfigurable platform built on open-source components that enhances validation, flexibility, and comprehensive evaluation of autonomous vehicle systems.

Findings

Enables first-of-a-kind trade studies on datasets and simulators

Supports longitudinal testing across multiple benchmark datasets

Facilitates V2I-collaboration case studies for multi-sensor, multi-agent algorithms

Abstract

Pioneers of autonomous vehicles (AVs) promised to revolutionize the driving experience and driving safety. However, milestones in AVs have materialized slower than forecast. Two culprits are (1) the lack of verifiability of proposed state-of-the-art AV components, and (2) stagnation of pursuing next-level evaluations, e.g., vehicle-to-infrastructure (V2I) and multi-agent collaboration. In part, progress has been hampered by: the large volume of software in AVs, the multiple disparate conventions, the difficulty of testing across datasets and simulators, and the inflexibility of state-of-the-art AV components. To address these challenges, we present AVstack, an open-source, reconfigurable software platform for AV design, implementation, test, and analysis. AVstack solves the validation problem by enabling first-of-a-kind trade studies on datasets and physics-based simulators. AVstack solves the stagnation problem as a reconfigurable AV platform built on dozens of open-source AV components in a high-level programming language. We demonstrate the power of AVstack through longitudinal testing across multiple benchmark datasets and V2I-collaboration case studies that explore trade-offs of designing multi-sensor, multi-agent algorithms.