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Freight transport prediction using electronic waybills and machine learning
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2014 (English)In: 2014 International Conference on Informative and Cybernetics for Computational Social Systems, IEEE Computer Society, 2014, 128-133 p.Conference paper (Refereed)
Abstract [en]

A waybill is a document that accompanies the freight during transportation. The document contains essential information such as, origin and destination of the freight, involved actors, and the type of freight being transported. We believe, the information from a waybill, when presented in an electronic format, can be utilized for building knowledge about the freight movement. The knowledge may be helpful for decision makers, e.g., freight transport companies and public authorities. In this paper, the results from a study of a Swedish transport company are presented using order data from a customer ordering database, which is, to a larger extent, similar to the information present in paper waybills. We have used the order data for predicting the type of freight moving between a particular origin and destination. Additionally, we have evaluated a number of different machine learning algorithms based on their prediction performances. The evaluation was based on their weighted average true-positive and false-positive rate, weighted average area under the curve, and weighted average recall values. We conclude, from the results, that the data from a waybill, when available in an electronic format, can be used to improve knowledge about freight transport. Additionally, we conclude that among the algorithms IBk, SMO, and LMT, IBk performed better by predicting the highest number of classes with higher weighted average values for true-positive and false-positive, and recall.

Place, publisher, year, edition, pages
IEEE Computer Society, 2014. 128-133 p.
Keyword [en]
machine learning; Waybill; freight mobility; IBk; SMO; LMT
National Category
Computer and Information Science
URN: urn:nbn:se:bth-10875DOI: 10.1109/ICCSS.2014.6961829ISI: 000358127600024ISBN: 978-1-4799-4753-9OAI: diva2:864097
International Conference on Informative and Cybernetics for Computational Social Systems, Qingdao, Shandong, China
Available from: 2015-10-25 Created: 2015-10-25 Last updated: 2016-04-07Bibliographically approved
In thesis
1. Designing Electronic Waybill Solutions for Road Freight Transport
Open this publication in new window or tab >>Designing Electronic Waybill Solutions for Road Freight Transport
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In freight transportation, a waybill is an important document that contains essential information about a consignment. The focus of this thesis is on a multi-purpose electronic waybill (e-Waybill) service, which can provide the functions of a paper waybill, and which is capable of storing, at least, the information present in a paper waybill. In addition, the service can be used to support other existing Intelligent Transportation System (ITS) services by utilizing on synergies with the existing services. Additionally, information entities from the e-Waybill service are investigated for the purpose of knowledge-building concerning freight flows.

A systematic review on state-of-the-art of the e-Waybill service reveals several limitations, such as limited focus on supporting ITS services. Five different conceptual e-Waybill solutions (that can be seen as abstract system designs for implementing the e-Waybill service) are proposed. The solutions are investigated for functional and technical requirements (non-functional requirements), which can potentially impose constraints on a potential system for implementing the e-Waybill service. Further, the service is investigated for information and functional synergies with other ITS services. For information synergy analysis, the required input information entities for different ITS services are identified; and if at least one information entity can be provided by an e-Waybill at the right location we regard it to be a synergy. Additionally, a service design method has been proposed for supporting the process of designing new ITS services, which primarily utilizes on functional synergies between the e-Waybill and different existing ITS services. The suggested method is applied for designing a new ITS service, i.e., the Liability Intelligent Transport System (LITS) service. The purpose of the LITS service isto support the process of identifying when and where a consignment has been damaged and who was responsible when the damage occurred. Furthermore, information entities from e-Waybills are utilized for building improved knowledge concerning freight flows. A freight and route estimation method has been proposed for building improved knowledge, e.g., in national road administrations, on the movement of trucks and freight.

The results from this thesis can be used to support the choice of practical e-Waybill service implementation, which has the possibility to provide high synergy with ITS services. This may lead to a higher utilization of ITS services and more sustainable transport, e.g., in terms of reduced congestion and emissions. Furthermore, the implemented e-Waybill service can be an enabler for collecting consignment and traffic data and converting the data into useful traffic information. In particular, the service can lead to increasing amounts of digitally stored data about consignments, which can lead to improved knowledge on the movement of freight and trucks. The knowledge may be helpful when making decisions concerning road taxes, fees, and infrastructure investments.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2016. 210 p.
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 4
Electronic waybill, e-waybill, Intelligent transport system, ITS services, Freight transport
National Category
Computer Systems Computer Science
urn:nbn:se:bth-11775 (URN)978-91-7295-326-0 (ISBN)
Public defence
2016-05-17, Ateljén, Biblioteksgatan 4, Karlshamn, 10:00 (English)
Available from: 2016-04-07 Created: 2016-03-30 Last updated: 2016-08-09Bibliographically approved

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