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Enhancing Autonomous Vehicles with Commonsense: Smart Mobility in Smart Cities

机译:用常识增强无人驾驶汽车:智慧城市中的智慧出行

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Recent advances in AI include a Law firm hiring a robot lawyer and companies developing autonomous vehicles with robot drivers. Findings from our study have gauged the current cognitive capacity of such systems, indicating areas for improvement. We focus on autonomous vehicles, i.e., those that conduct automated driving and need to make autonomous, i.e., independent decisions. We propose an approach enabled with commonsense knowledge (CSK) from worldwide repositories to simulate intuitive humanlike decision-making in autonomous vehicles. We consider the repository WebChild with a multitude of CSK concepts, properties and relations. We investigate this and related domain-specific knowledge bases (domain KBs) to harness them within our proposed approach. Accordingly we build a transportation domain KB incorporating CSK and the needs of autonomous vehicles. This would be useful in guiding automated driving and making the systems get closer to the thresholds of human cognition. This work thereby makes contributions to smart mobility in smart cities. The paper presents our vision with design, implementation, experiments, recommendations and a future roadmap. As a broader impact, it propels more joint work between AI, Law and related areas.
机译:人工智能的最新进展包括一家律师事务所聘请机器人律师,以及一些开发有机器人驾驶员的自动驾驶汽车的公司。我们的研究结果评估了此类系统的当前认知能力,指出了需要改进的地方。我们专注于自动驾驶汽车,即进行自动驾驶并需要做出自动驾驶(即独立决策)的车辆。我们提出了一种方法,该方法具有来自全球知识库的常识知识(CSK),可模拟自动驾驶汽车中直观的类人决策。我们认为存储库WebChild具有许多CSK概念,属性和关系。我们研究了此和相关领域特定的知识库(领域KB),以在我们提出的方法中利用它们。因此,我们建立了一个包含CSK和自动驾驶汽车需求的运输领域知识库。这将有助于引导自动驾驶并使系统更接近人类认知的阈值。因此,这项工作为智慧城市中的智慧出行做出了贡献。本文通过设计,实施,实验,建议和未来路线图展示了我们的愿景。作为更广泛的影响,它推动了AI,法律和相关领域之间的更多合作。

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