Freeway Travel Time Information From Input- Output Vehicle Counts: A Drift Correction Method Based on AVI Data

نویسندگان

چکیده

Input-output cumulative count curves are a powerful tool to forecast freeway travel times in the very short term, as they rely on predictive information given by vehicles' accumulation target section. Therefore, could represent appealing method feed real-time traffic systems. However, detectors' drift implies poor accuracy estimation of accumulation, leading completely unreliable time predictions. A correction is necessary. In contrast, several technologies allow accurate direct measurements, like automatic vehicle identification (AVI) or tracking all cases, measurements obtained once has crossed This means that representative near past conditions, while objective systems transmit about conditions future. this context, present paper aims fuse provided input-output diagrams, from loop detectors, with AVI measurements. fusion allows exploiting correct detectors. Then, corrected can be used obtain reliable short-term predictions times. The proposed data been applied test site AP7 Barcelona, obtaining significantly better results than common practices simply disseminating using spot-speed methods.

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ژورنال

عنوان ژورنال: IEEE Transactions on Intelligent Transportation Systems

سال: 2021

ISSN: ['1558-0016', '1524-9050']

DOI: https://doi.org/10.1109/tits.2020.2992300