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Special issue on car navigation and vehicle systems

机译:汽车导航和车辆系统特刊

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摘要

From the early experiments on self-driving vehicles half a century ago to the modern Google driverless cars, significant progress has been made in the understanding of traffic scenes and extracting of information that the autonomous cars need. In addition to guidance and improved comfort, advanced navigation systems also provide enhanced driver assistance to maintain a safe speed, keep a safe distance, drive within the lane, avoid overtaking in critical situations, safely pass intersections, avoid collisions with vulnerable road users, and as a last resort, reduce the severity of an accident if it still occurs. Yet, automatic detection of such objects and events comes with many challenges. Complex backgrounds, low-visibility weather conditions, cast shadows, strong headlights, direct sunlight during dusk and dawn, uneven street illumination, occlusion caused by other vehicles, great variation of traffic sign pictograms are just some of the issues that make these tasks difficult.
机译:从半个世纪前的无人驾驶汽车的早期实验到现代的Google无人驾驶汽车,在了解交通场景和提取自动驾驶汽车所需的信息方面已经取得了重大进展。除了引导和改善的舒适度之外,先进的导航系统还提供增强的驾驶员辅助功能,以保持安全的速度,保持安全的距离,在车道内行驶,避免在紧急情况下超车,安全地通过交叉路口,避免与脆弱的道路使用者发生碰撞以及作为最后的选择,如果事故仍然发生,请降低严重性。然而,对此类对象和事件的自动检测面临许多挑战。复杂的背景,低能见度的天气条件,阴影,强烈的头灯,黄昏和黎明时的直射阳光,不均匀的街道照明,其他车辆造成的遮挡,交通标志象形图的巨大变化,这些都是使这些任务变得困难的问题。

著录项

  • 来源
    《Machine Vision and Applications》 |2014年第3期|545-546|共2页
  • 作者

    Fatih Porikli; Luc Van Gool;

  • 作者单位

    Australian National University, Canberra, Australia;

    Eidgenoessische Technische Hochschule Zuerich (ETH Zurich), Zurich, Switzerland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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