A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands

Alexandra G.J. Vegelien; Elenna R. Dugundji

doi:10.1109/ITSC.2018.8569509

A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands

Alexandra G.J. Vegelien
, Elenna R. Dugundji

Mathematics

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

This paper presents one of the first discrete choice models regarding truck departure time for road freight transport using revealed preference electronic trace data. The data containing 1447 logistical routes was obtained from GPS units in trucks of a large European retailer in June 2016. Detailed historical link speed data of the road network is used to compute trip durations for non-chosen departure times for each specific recorded route. A baseline multinomial logit model is initially estimated solely based upon trip duration as an explanatory variable. Next, product type is added as an observed variable, improving the multinomial logit model fit. Finally, the model is flexibly extended to incorporate unobserved heterogeneity by nesting departure time alternatives into time blocks for morning, afternoon, and night, further improving the model fit.

Original language	English
Title of host publication	2018 21st Intelligent Transportation Systems Conference (ITSC)
Publisher	Institute of Electrical and Electronics Engineers, Inc.
Pages	1770-1774
Number of pages	5
ISBN (Electronic)	9781728103235
ISBN (Print)	9781728103211
DOIs	https://doi.org/10.1109/ITSC.2018.8569509
Publication status	Published - 9 Dec 2018
Event	21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States Duration: 4 Nov 2018 → 7 Nov 2018

Conference

Conference	21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
Country/Territory	United States
City	Maui
Period	4/11/18 → 7/11/18

Funding

* The data collection was made possible via a grant from the Netherlands Organisation for Scientific Research (NWO) for the ITSLOG project.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Access to Document

10.1109/ITSC.2018.8569509

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Cite this

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title = "A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands",

abstract = "This paper presents one of the first discrete choice models regarding truck departure time for road freight transport using revealed preference electronic trace data. The data containing 1447 logistical routes was obtained from GPS units in trucks of a large European retailer in June 2016. Detailed historical link speed data of the road network is used to compute trip durations for non-chosen departure times for each specific recorded route. A baseline multinomial logit model is initially estimated solely based upon trip duration as an explanatory variable. Next, product type is added as an observed variable, improving the multinomial logit model fit. Finally, the model is flexibly extended to incorporate unobserved heterogeneity by nesting departure time alternatives into time blocks for morning, afternoon, and night, further improving the model fit.",

author = "Vegelien, \{Alexandra G.J.\} and Dugundji, \{Elenna R.\}",

year = "2018",

month = dec,

day = "9",

doi = "10.1109/ITSC.2018.8569509",

language = "English",

isbn = "9781728103211",

pages = "1770--1774",

booktitle = "2018 21st Intelligent Transportation Systems Conference (ITSC)",

publisher = "Institute of Electrical and Electronics Engineers, Inc.",

note = "21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 ; Conference date: 04-11-2018 Through 07-11-2018",

}

Vegelien, AGJ & Dugundji, ER 2018, A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands. in 2018 21st Intelligent Transportation Systems Conference (ITSC)., 8569509, Institute of Electrical and Electronics Engineers, Inc., pp. 1770-1774, 21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018, Maui, United States, 4/11/18. https://doi.org/10.1109/ITSC.2018.8569509

A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands. / Vegelien, Alexandra G.J.; Dugundji, Elenna R.
2018 21st Intelligent Transportation Systems Conference (ITSC). Institute of Electrical and Electronics Engineers, Inc., 2018. p. 1770-1774 8569509.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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N2 - This paper presents one of the first discrete choice models regarding truck departure time for road freight transport using revealed preference electronic trace data. The data containing 1447 logistical routes was obtained from GPS units in trucks of a large European retailer in June 2016. Detailed historical link speed data of the road network is used to compute trip durations for non-chosen departure times for each specific recorded route. A baseline multinomial logit model is initially estimated solely based upon trip duration as an explanatory variable. Next, product type is added as an observed variable, improving the multinomial logit model fit. Finally, the model is flexibly extended to incorporate unobserved heterogeneity by nesting departure time alternatives into time blocks for morning, afternoon, and night, further improving the model fit.

AB - This paper presents one of the first discrete choice models regarding truck departure time for road freight transport using revealed preference electronic trace data. The data containing 1447 logistical routes was obtained from GPS units in trucks of a large European retailer in June 2016. Detailed historical link speed data of the road network is used to compute trip durations for non-chosen departure times for each specific recorded route. A baseline multinomial logit model is initially estimated solely based upon trip duration as an explanatory variable. Next, product type is added as an observed variable, improving the multinomial logit model fit. Finally, the model is flexibly extended to incorporate unobserved heterogeneity by nesting departure time alternatives into time blocks for morning, afternoon, and night, further improving the model fit.

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A Revealed Preference Time of Day Model for Departure Time of Delivery Trucks in the Netherlands

Abstract

Conference

Funding

UN SDGs

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