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.
翻译:自动驾驶车(AV)的先驱者(AV)曾承诺使驾驶经验和驾驶安全发生革命性变革,然而,AV的里程碑比预测的要慢。有两个罪魁祸首是:(1) 缺乏对拟议最先进的AV组件的可核查性,(2) 对AV设计、实施、测试和分析的开放源码、可重新配置的软件平台,例如车辆到基础设施(V2I)和多试剂合作等,在下一个层次进行评估方面停滞不前。部分进展受到以下因素的阻碍:AV的软件量大,多种不同的公约,测试数据集和模拟器的难度,以及最新AVV组件的不灵活性。为了应对这些挑战,我们介绍了AVastack,这是用于AVVV设计、实施、测试和分析的开放源、可重新配置的软件平台。AVStack解决了验证问题,方法是对数据集和基于物理模拟的模拟器进行首次贸易研究。AVtack解决了停滞问题,作为可重新配置的AVV平台,我们以数十个开放源的AVV权力组件为基础,在高层次的AVAV级数据库的多层测试中进行测试。</s>