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A Data Mining Approach on Lorry Drivers Overloading in Tehran Urban Roads
Joint Authors
Ayazi, Ehsan
Sheikholeslami, Abdolreza
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-10
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The aim of this study is to identify the important factors influencing overloading of commercial vehicles on Tehran’s urban roads.
The weight information of commercial freight vehicles was collected using a pair of portable scales besides other information needed including driver information, vehicle features, load, and travel details by completing a questionnaire.
The results showed that the highest probability of overloading is for construction loads.
Further, the analysis of the results in the lorry type section shows that the least likely occurrence of overloading is among pickup truck drivers such that this likelihood within this group was one-third among Nissan and small truck drivers.
Also, the results of modeling the type of route showed that the highest likelihood of overloading is for internal loads (origin and destination inside Tehran), and the least probability of overloading is for suburban trips (origin and destination outside of Tehran).
Considering the type of load packing as a variable, the results of binary regression model analysis showed that the most probability of overloading occurs for packed (boxed) loads.
Finally, it was concluded that drivers are 18 times more likely to commit overloading on weekends than on weekdays.
American Psychological Association (APA)
Ayazi, Ehsan& Sheikholeslami, Abdolreza. 2020. A Data Mining Approach on Lorry Drivers Overloading in Tehran Urban Roads. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1175935
Modern Language Association (MLA)
Ayazi, Ehsan& Sheikholeslami, Abdolreza. A Data Mining Approach on Lorry Drivers Overloading in Tehran Urban Roads. Journal of Advanced Transportation No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1175935
American Medical Association (AMA)
Ayazi, Ehsan& Sheikholeslami, Abdolreza. A Data Mining Approach on Lorry Drivers Overloading in Tehran Urban Roads. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1175935
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175935