Improving the Prediction of Passenger Numbers in Public Transit Networks by Combining Short-Term Forecasts With Real-Time Occupancy Data

Improving the Prediction of Passenger Numbers in Public Transit Networks by Combining Short-Term Forecasts With Real-Time Occupancy Data

Passengers of public transportation nowadays expect reliable and accurate travel information. The need for occupancy information is becoming more prevalent in intelligent public transport systems as people started avoiding overcrowded vehicles during the COVID-19 pandemic. Furthermore, public transp...

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Bibliographic Details
Main Authors: Josef Hoppe, Felix Schwinger, Henrik Haeger, Jonas Wernz, Matthias Jarke
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
Subjects:
Clustering algorithms
predictive models
public transportation
time series analysis
Online Access:https://ieeexplore.ieee.org/document/10057448/

Internet

https://ieeexplore.ieee.org/document/10057448/

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