Estimation of Passenger Flow in a Bus Route using Kalman Filter

This paper summarizes the idea of passenger flow estimation using Kalman Filter. It is always beneficial if the buses are coming at the proper times and thus reducing the waiting time of passengers. The arrival of buses, passenger flow, traffic flow are all random phenomena. The passenger flow can b...

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Bibliographic Details
Published in2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) pp. 1248 - 1251
Main Authors Vidya, G.S., Hari, V.S., Shivasagaran, Suryakumar
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2020
Subjects
Analytical models
Autoregressive processes
Data models
Estimation
Geometric Brownian motion
Kalman filter
Kalman filters
Mathematical model
Prediction
Predictive models
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Summary:This paper summarizes the idea of passenger flow estimation using Kalman Filter. It is always beneficial if the buses are coming at the proper times and thus reducing the waiting time of passengers. The arrival of buses, passenger flow, traffic flow are all random phenomena. The passenger flow can be modelled as a Geometric Brownian motion. The estimation of passenger flow in any route is beneficial for the proper scheduling of buses, while maintaining an apparent rise in the bottom line of bus operators. The Kalman Filtering model is used to estimate the passenger data.
ISBN:1728151961
9781728151960
ISSN:2575-7288
DOI:10.1109/ICACCS48705.2020.9074363