Multiple Objects Tracking using Radar for Autonomous Driving

Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, M. Jeon
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引用次数: 10

Abstract

Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.
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基于雷达的自动驾驶多目标跟踪
目标检测与跟踪是感知时空环境的重要组成部分。相机和激光雷达作为主要的传感器模式,其可用性和可负担性已在研究中用于目标检测和跟踪。使用相机和激光雷达进行目标检测和跟踪的深度学习算法已经说明了有希望的结果,但这些传感器模式容易受到天气条件的影响,数据稀疏,空间分辨率问题。在这项工作中,我们探讨了使用雷达探测远距离目标和跟踪的问题。为了提高我们所提出的工作的有效性,我们使用我们的自动驾驶汽车试验台在不同的交通场景中进行了大量的实验。
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