Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105279
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Aeronautical and Aviation Engineering | - |
dc.creator | Yan, M | - |
dc.creator | Xie, B | - |
dc.creator | Xu, G | - |
dc.date.accessioned | 2024-04-12T06:51:14Z | - |
dc.date.available | 2024-04-12T06:51:14Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/105279 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Yan M, Xie B, Xu G. Identifying Spatial–Temporal Characteristics and Significant Factors of Bus Bunching Based on an eGA and DT Model. Applied Sciences. 2022; 12(22):11778 is available at https://doi.org/10.3390/app122211778. | en_US |
dc.subject | Automatic vehicle location | en_US |
dc.subject | Bus bunching | en_US |
dc.subject | Bus headway | en_US |
dc.subject | Decision tree | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Spatial–temporal characteristics | en_US |
dc.title | Identifying spatial-temporal characteristics and significant factors of bus bunching based on an eGA and DT model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 12 | - |
dc.identifier.issue | 22 | - |
dc.identifier.doi | 10.3390/app122211778 | - |
dcterms.abstract | Bus bunching is a common phenomenon caused by irregular bus headway, which increases the passenger waiting time, makes the passenger capacity uneven, and severely reduces the reliability of bus service. This paper clarified the process of bus bunching formation, analyzed the variation characteristics of bus bunching in a single day, in different types of periods, and at different bus stops, then concluded twelve potential factors. A hybrid model integrating a genetic algorithm with elitist preservation strategy (eGA) and decision tree (DT) was proposed. The eGA part constructs the model framework and transforms the factor identification into a problem of selecting the fittest individual from the population, while the DT part evaluates the fitness. Model verification and comparison were conducted based on real automatic vehicle location (AVL) data in Shenzhen, China. The results showed that the proposed eGA–DT model outperformed other frequently used single DT and extra tree (ET) models with at least a 20% reduction in MAE under different bus routes, periods, and bus stops. Six factors, including the sequence of the bus stop, the headway and dwell time at the previous bus stop, the travel time between bus stops, etc., were identified to have a significant effect on bus bunching, which is of great value for feature selection to improve the accuracy and efficiency of bus bunching prediction and real-time bus dispatching. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Applied sciences, Nov. 2022, v. 12, no. 22, 11778 | - |
dcterms.isPartOf | Applied sciences | - |
dcterms.issued | 2022-11 | - |
dc.identifier.scopus | 2-s2.0-85142830948 | - |
dc.identifier.eissn | 2076-3417 | - |
dc.identifier.artn | 11778 | - |
dc.description.validate | 202403 bcvc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China; Science and Technology Innovation Committee of Shenzhen | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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applsci-12-11778.pdf | 5.68 MB | Adobe PDF | View/Open |
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