交通普查中用于车辆统计的视频摄像技术:问题、策略与机遇

Q2 Social Sciences Planning Malaysia Pub Date : 2023-08-31 DOI:10.21837/pm.v21i28.1316
K. K. Mohd Shariff, Megat Qamarul Zaffi Megat Ali, A. H. Jahidin, M. S. A. Megat Ali, A. I. Mohd Yassin
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引用次数: 0

摘要

本研究概述了通常用于自动车辆分类和计数的传感器技术,重点是非侵入式传感器。视频摄像机是交通普查中最可行的数据采集解决方案,因为它可以在便携式模式下操作,并且可以在任何地点使用。为了确保计数准确,必须考虑几个因素。其中包括摄像头的最佳位置,以确保所有车辆都能被观察到,并且必须考虑照明条件,以确保良好的视频质量。这些进一步有助于通过专用的深度学习算法对车辆进行准确的分类和计数。由于数据收集可能涉及云计算和存储访问能力较差的位置,因此建议离线处理。该研究还揭示了解决视频摄像机战略布局和专用深度学习算法开发相关问题的机会。
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VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
This study provides an overview of the sensor technologies commonly used for automated vehicle classification and counting, with a focus on non-intrusive sensors. Video cameras are found to be the most feasible solution for data collection in traffic census as it can operate in portable mode and used at any location. Several factors must be considered to ensure accurate counting. These involve optimum placement of the camera to ensure that all vehicles can be observed, and the lighting conditions must be considered to ensure good video quality. These further contributes to accurate classification and counting of vehicles by dedicated deep learning algorithm. As the data collection may involve location with poor access to cloud computing and storage, offline processing is therefore recommended. The study also revealed opportunities for solving issues related to strategic placement of video cameras, and development of dedicated deep learning algorithms.
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来源期刊
Planning Malaysia
Planning Malaysia Social Sciences-Urban Studies
CiteScore
1.40
自引率
0.00%
发文量
68
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