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Sustainable public transportation using markov chains: case study Hamburg public transportation
Citation Link: https://doi.org/10.15480/882.3998
Publikationstyp
Conference Paper
Date Issued
2021-12-01
Sprache
English
Author(s)
Herausgeber*innen
TORE-DOI
First published in
Number in series
32
Start Page
97
End Page
134
Citation
Hamburg International Conference of Logistics (HICL) 32: 97-134 (2021)
Contribution to Conference
Publisher
epubli
Peer Reviewed
true
Purpose: Intelligent public transportation systems have been largely focused on improving the planning, and monitoring the transportation flows during recent years. Advancements in public transportation systems increase service levels and encourage more usage of public transportation. The forecast of buses' arrival time to stations and having a dynamic system to anticipate the real-time possible events for users, significantly increase passenger satisfaction. This paper has studied the literature considering dynamic public transportation systems and also matters of environmental emissions.
Methodology: The paper has developed a method to predict bus arrivals at stations by considering the buses’ operation parameters and variables with stochastic characteristics by applying Markov Chains. The paper also applied the assignment problem technique and multi-objective planning to enable a framework for public transportation resource assignment considering the perspectives mentioned earlier.
Findings: The real data of Hamburg public transportation has been used to verify the capabilities of the platform. The findings show that the model validity of the platform and enabled effective strategic planning for public resource assignment.
Originality: This paper has studied the related literature and discussed the considerable gap for proposing a dynamic public transportation system that brings satisfaction from the side of the users and also mutually minimizing environmental emissions.
Methodology: The paper has developed a method to predict bus arrivals at stations by considering the buses’ operation parameters and variables with stochastic characteristics by applying Markov Chains. The paper also applied the assignment problem technique and multi-objective planning to enable a framework for public transportation resource assignment considering the perspectives mentioned earlier.
Findings: The real data of Hamburg public transportation has been used to verify the capabilities of the platform. The findings show that the model validity of the platform and enabled effective strategic planning for public resource assignment.
Originality: This paper has studied the related literature and discussed the considerable gap for proposing a dynamic public transportation system that brings satisfaction from the side of the users and also mutually minimizing environmental emissions.
Subjects
City Logistics
DDC Class
330: Wirtschaft
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Name
Sodachi and Fatahi Valilai (2021) - Sustainable Public Transportation using Markov Chains_Case Study Hamburg Public Transportation.pdf
Size
1.34 MB
Format
Adobe PDF