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

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
Main Authors: Mohammad A. Aljamal, Hossam M. Abdelghaffar, Hesham A. Rakha
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Sensors
Subjects:
real-time estimation
probe vehicle
traffic density
neural network
level of market penetration rate
Online Access:https://www.mdpi.com/1424-8220/19/19/4325

Internet

https://www.mdpi.com/1424-8220/19/19/4325

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