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EureCar turbo: A self-driving car that can handle adverse weather conditions

机译:EureCar turbo:可应对恶劣天气条件的自动驾驶汽车

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Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operational under amiable weather conditions, i.e., on sunny days on dry roads. In order to enable autonomous cars to handle adverse driving conditions such as rain and wet roads, the algorithm must be able to detect roads within a tolerable margin of error using sensors such as cameras and laser scanners. In this paper, we propose a sensor fusion algorithms that is able to operate under a variety of weather conditions, including rain. Our algorithm was validated when a strong shower occurred during the 2014 Hyundai Motor Company's Autonomous Car Competition. In this paper, we present the competition results that were collected on the same course on both sunny and rainy days. Based on the comparison, we propose the future directions to improve the autonomous driving capability under adverse environmental conditions.
机译:近年来,自动驾驶技术取得了长足的进步。为了使自动驾驶汽车变得实用,即使在不利的驾驶条件下,也要求它们安全可靠地运行。然而,目前大多数自动驾驶汽车仅在友好的天气条件下,即在干燥道路上的晴天才可使用。为了使自动驾驶汽车能够应对恶劣的驾驶条件(例如雨天和潮湿的道路),该算法必须能够使用传感器(例如相机和激光扫描仪)在可容忍的误差范围内检测道路。在本文中,我们提出了一种传感器融合算法,该算法能够在包括雨水在内的多种天气条件下运行。 2014年现代汽车公司的自动驾驶汽车竞赛中发生强烈阵雨时,我们的算法得到了验证。在本文中,我们介绍了在晴天和雨天在同一路线上收集的比赛结果。在比较的基础上,我们提出了在不利环境条件下提高自动驾驶能力的未来方向。

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