Ubiquitous Traffic Volume Estimation through Machine Learning Procedure [electronic resource]

• Ngôn ngữ: eng
• Ký hiệu phân loại: 621.39 Computer engineering
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Office of the Assistant Secretary of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2019
• Mô tả vật lý: Size: 1.5 MB : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 256164
• Chủ đề: 1. 30 direct energy conversion; 2. 47 other instrumentation; 3. Machine learning models; 4. Probe vehicle data; 5. Traffic; 6. Volume estimation

Tóm tắt

High-quality traffic volume data is critical for transportation planning, operations, and travel-energy calculations. However, vehicle count data from roadside sensors is very sparse owing to high capital cost of installing, and on-going maintenance of electronic sensor equipment. This research effort aims to bring to market a first of its kind traffic volume data product that provides accurate estimates of traffic volumes across the entire road network for all times (24x7) and all locations (100% coverage). This product greatly improves the coverage and quality of traffic volume information by combining commercial probe traffic data with traditional traffic measurement using state-of-the-art machine learning. Commercial probe traffic data are derived from vehicles that self-report their position and speed as well as crowd sourced data from smartphone applications.