Identifying tour structures in freight transport by mining of large trip databases

Ali Nadi; Hans van Lint; Lorant Tavasszy; Maaike Snelder

doi:10.1109/ITSC45102.2020.9294432

Identifying tour structures in freight transport by mining of large trip databases

Ali Nadi , Hans van Lint, Lorant Tavasszy, Maaike Snelder

Transport and Planning

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Scheduling and Routing in freight transport are usually the end products of an optimization process. However, the results may differ due to the heterogeneity of rules in different transport markets. Since the understanding of these decision rules is important for disaggregate freight modeling, this paper investigates the development of an effective decision tree method for extracting them from an extensive freight transport data. We applied the method to model departure time and type of tours in freight transport of agricultural products. Having these two models together help us understand the whole anatomy of the freight activities for the selected transport segment. The models highlight the characteristics of time-of-day freight activities for this sector and indicate the importance of spatial and temporal characteristics in capturing the distinctions of the type of tours.

Original language	English
Title of host publication	2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
Publisher	IEEE
Number of pages	7
ISBN (Electronic)	978-1-7281-4149-7
ISBN (Print)	978-1-7281-4150-3
DOIs	https://doi.org/10.1109/ITSC45102.2020.9294432
Publication status	Published - 2020
Event	The 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020) - Rhodes, Greece Duration: 20 Sep 2020 → 23 Sep 2020 https://www.ieee-itsc2020.org/

Conference

Conference	The 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020)
Country	Greece
City	Rhodes
Period	20/09/20 → 23/09/20
Internet address	https://www.ieee-itsc2020.org/

Access to Document

10.1109/ITSC45102.2020.9294432

Link to publication in Scopus

Embargoed Document

09294432
Final published version, 620 KB
Embargo ends: 24/06/21

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@inproceedings{e11d8040ac2f4df381626fecd2924dae,

title = "Identifying tour structures in freight transport by mining of large trip databases",

abstract = "Scheduling and Routing in freight transport are usually the end products of an optimization process. However, the results may differ due to the heterogeneity of rules in different transport markets. Since the understanding of these decision rules is important for disaggregate freight modeling, this paper investigates the development of an effective decision tree method for extracting them from an extensive freight transport data. We applied the method to model departure time and type of tours in freight transport of agricultural products. Having these two models together help us understand the whole anatomy of the freight activities for the selected transport segment. The models highlight the characteristics of time-of-day freight activities for this sector and indicate the importance of spatial and temporal characteristics in capturing the distinctions of the type of tours.",

author = "Ali Nadi and {van Lint}, Hans and Lorant Tavasszy and Maaike Snelder",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; The 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020) ; Conference date: 20-09-2020 Through 23-09-2020",

year = "2020",

doi = "10.1109/ITSC45102.2020.9294432",

language = "English",

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booktitle = "2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020",

publisher = "IEEE ",

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url = "https://www.ieee-itsc2020.org/",

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Nadi , A , van Lint, H , Tavasszy, L & Snelder, M 2020, Identifying tour structures in freight transport by mining of large trip databases. in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020., 9294432, IEEE , The 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020), Rhodes, Greece, 20/09/20. https://doi.org/10.1109/ITSC45102.2020.9294432

Identifying tour structures in freight transport by mining of large trip databases. / Nadi , Ali ; van Lint, Hans ; Tavasszy, Lorant ; Snelder, Maaike.

2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. IEEE , 2020. 9294432.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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N2 - Scheduling and Routing in freight transport are usually the end products of an optimization process. However, the results may differ due to the heterogeneity of rules in different transport markets. Since the understanding of these decision rules is important for disaggregate freight modeling, this paper investigates the development of an effective decision tree method for extracting them from an extensive freight transport data. We applied the method to model departure time and type of tours in freight transport of agricultural products. Having these two models together help us understand the whole anatomy of the freight activities for the selected transport segment. The models highlight the characteristics of time-of-day freight activities for this sector and indicate the importance of spatial and temporal characteristics in capturing the distinctions of the type of tours.

AB - Scheduling and Routing in freight transport are usually the end products of an optimization process. However, the results may differ due to the heterogeneity of rules in different transport markets. Since the understanding of these decision rules is important for disaggregate freight modeling, this paper investigates the development of an effective decision tree method for extracting them from an extensive freight transport data. We applied the method to model departure time and type of tours in freight transport of agricultural products. Having these two models together help us understand the whole anatomy of the freight activities for the selected transport segment. The models highlight the characteristics of time-of-day freight activities for this sector and indicate the importance of spatial and temporal characteristics in capturing the distinctions of the type of tours.

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