一种灵活的自动驾驶agent-人机交互测试虚拟环境

G. Grasso, Giovanni d’Italia, S. Battiato
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引用次数: 2

摘要

近年来,由于汽车制造商的商业兴趣,自动驾驶汽车获得了相当大的吸引力,他们预计自动驾驶汽车将在未来十年得到广泛应用。研究主要集中在特定的主题上,这些主题可以使自动驾驶汽车(AVs)的鲁棒人工自主代理的可行性,范围从人工视觉到自动环境感知和推理,agent-agent交互以及传感器增强和集成。在评估人类与自动驾驶汽车的互动方面,以及在确定自动驾驶汽车与人类驾驶员打交道时可接受的交战规则方面,研究的力度有所减少。未来几年,随着5级自动驾驶汽车出现在我们的街道上,自动驾驶的这一方面将变得极其重要,而大多数汽车仍将由人类驾驶。为了通过实验来评估自动驾驶汽车如何成功地与人类驾驶员互动,我们建立了一个实验室装置,可以模拟人类驾驶员遇到自动驾驶汽车并与之互动的各种情况。基于Unity游戏引擎,我们开发了一个城市环境,其中自动驾驶汽车与人类驾驶的汽车、行人和各种代理进行交互。这种设置允许人类受试者在虚拟现实(VR)环境中驾驶,并评估他们在与其他人类驾驶员和自动驾驶汽车互动期间的行为。目标是定义一套可应用于自动驾驶设计的规则,使自动驾驶汽车对人类驾驶员做出反应,同时考虑到人类驾驶员在真实环境中表现出的行为模式和对交通规则的不同尊重。我们提出了一个早期的实验设置,可能有助于以定量和可重复的方式理解这种方法如何有助于设计更适合大规模部署的自动驾驶汽车。
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A flexible virtual environment for autonomous driving agent-human interaction testing
Autonomous driving has, in recent years, gained considerable traction due to commercial interest by car manufacturers, that envision a widespread use of self-driving cars in the next decade. Research has mainly focused on specific topics, that can enable the feasibility of robust artificial autonomous agents for autonomous vehicles (AVs), ranging from artificial vision, to automatic environmental sensing and inference, agent-agent interaction and sensor augmentation and integration. A somewhat reduced effort has been directed towards the evaluation of human-AV interaction and in the direction of defining acceptable rules of engagement when AV deal with human drivers. This aspect of autonomous driving will became extremely relevant in the next years as level 5 AVs will make their appearance on our streets and most of the cars will still be driven by humans. To assess, experimentally, how AVs can successfully interact with human drivers we have constructed a lab setup, which can simulate a large range of situations in which human drivers encounter AVs and interact with them. Based on the Unity Gaming Engine an urban environment has been developed where AVs interact with human driven cars, pedestrians and various agents. This setup allows for human subjects to drive in a virtual reality (VR) environment, and assess their behavior during the interaction with other human drivers and AVs. The goal is to define a set of rules that can be applied in AV design, to make autonomous cars react to human drivers, taking into account the behavioral patterns and variable respect of traffic regulations that human drivers exhibit in real environments. We present an early experimental setup, potentially useful for understanding, in a quantitative and reproducible way, how this approach can contribute in designing AVs that are more suited for large scale deployment.
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