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

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-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 languageEnglish
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PublisherIEEE
Number of pages7
ISBN (Electronic)978-1-7281-4149-7
ISBN (Print)978-1-7281-4150-3
DOIs
Publication statusPublished - 2020
EventThe 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020) - Rhodes, Greece
Duration: 20 Sep 202023 Sep 2020
https://www.ieee-itsc2020.org/

Conference

ConferenceThe 23rd IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2020)
CountryGreece
CityRhodes
Period20/09/2023/09/20
Internet address

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