Developing a Neural–Kalman Filtering Approach for Estimating Traffic Stream Density Using Probe Vehicle Data

This paper presents a novel model for estimating the number of vehicles along signalized approaches. The proposed estimation algorithm utilizes the adaptive Kalman filter (AKF) to produce reliable traffic vehicle count estimates, considering real-time estimates of the system noise characteristics. T...

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Bibliographic Details
Published in:	Sensors (Basel)
Main Authors:	Aljamal, Mohammad A., Abdelghaffar, Hossam M., Rakha, Hesham A.
Format:	Artigo
Language:	Inglês
Published:	MDPI 2019
Subjects:	Article
Online Access:	https://ncbi.nlm.nih.gov/pmc/articles/PMC6806210/ https://ncbi.nlm.nih.gov/pubmed/31591292 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19194325
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Developing a Neural–Kalman Filtering Approach for Estimating Traffic Stream Density Using Probe Vehicle Data

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