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Advanced framework for microscopic and lane‐level macroscopic traffic parameters estimation from UAV video

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العنوان: Advanced framework for microscopic and lane‐level macroscopic traffic parameters estimation from UAV video
المؤلفون: Ke, Ruimin, Feng, Shuo, Cui, Zhiyong, Wang, Yinhai
بيانات النشر: Wiley Periodicals, Inc.
The Institution of Engineering and Technology
سنة النشر: 2020
المجموعة: University of Michigan: Deep Blue
مصطلحات موضوعية: microscopic lane‐level macroscopic traffic parameters estimation, modern traffic sensing research, UAV‐based traffic sensing, aggregated macroscopic traffic data, higher‐resolution traffic data, traffic patterns, traffic flow characteristics, real‐world UAV video data, advanced traffic management, UAV video features, (B6135) Optical, image and video signal processing, (C3390C) Mobile robots, (C5260B) Computer vision and image processing techniques, (C5260D) Video signal processing, (C7445) Traffic engineering computing, parameter estimation, autonomous aerial vehicles, road vehicles, road traffic, object detection, traffic engineering computing, video signal processing, robot vision, advanced traffic sensing, aggregated macroscopic traffic parameters, Computer Science, Engineering
الوصف: Peer Reviewed ; http://deepblue.lib.umich.edu/bitstream/2027.42/166282/1/itr2bf00873.pdf
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: unknown
تدمد: 1751-956X
1751-9578
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DOI: 10.1049/iet-its.2019.0463
DOI: 10.7302/205
الاتاحة: https://hdl.handle.net/2027.42/166282
https://doi.org/10.1049/iet-its.2019.0463
https://doi.org/10.7302/205
Rights: IndexNoFollow
رقم الانضمام: edsbas.36F1049F
قاعدة البيانات: BASE
الوصف
تدمد:1751956X
17519578
DOI:10.1049/iet-its.2019.0463