Heavy commercial vehicles' mobility: Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)

Georg Balke; Lennart Adenaw

doi:10.1016/j.dib.2023.109246

Heavy commercial vehicles' mobility: Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)

Georg Balke
, Lennart Adenaw

Chair of Automotive Technology

Technical University of Munich

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

During a period of 7 months, 54 class N3 trucks from 4 fleets of German fleet operators were equipped with high resolution GPS data loggers. A total of 1.26 million km of driving data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of heavy commercial vehicles. This dataset provides metadata of recorded tracks as well as high-resolution time series data of the vehicle speed. Its applications include simulation of electrification for heavy commercial vehicles, modeling logistics processes or driving cycle construction.

Original language	English
Article number	109246
Journal	Data in Brief
Volume	48
DOIs	https://doi.org/10.1016/j.dib.2023.109246
State	Published - Jun 2023

Keywords

Fleet data
GNSS
Logistics
Mobility data
Road freight transport
Truck

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10.1016/j.dib.2023.109246

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title = "Heavy commercial vehicles' mobility: Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)",

abstract = "During a period of 7 months, 54 class N3 trucks from 4 fleets of German fleet operators were equipped with high resolution GPS data loggers. A total of 1.26 million km of driving data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of heavy commercial vehicles. This dataset provides metadata of recorded tracks as well as high-resolution time series data of the vehicle speed. Its applications include simulation of electrification for heavy commercial vehicles, modeling logistics processes or driving cycle construction.",

keywords = "Fleet data, GNSS, Logistics, Mobility data, Road freight transport, Truck",

author = "Georg Balke and Lennart Adenaw",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

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doi = "10.1016/j.dib.2023.109246",

language = "English",

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T2 - Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)

AU - Balke, Georg

AU - Adenaw, Lennart

PY - 2023/6

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N2 - During a period of 7 months, 54 class N3 trucks from 4 fleets of German fleet operators were equipped with high resolution GPS data loggers. A total of 1.26 million km of driving data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of heavy commercial vehicles. This dataset provides metadata of recorded tracks as well as high-resolution time series data of the vehicle speed. Its applications include simulation of electrification for heavy commercial vehicles, modeling logistics processes or driving cycle construction.

AB - During a period of 7 months, 54 class N3 trucks from 4 fleets of German fleet operators were equipped with high resolution GPS data loggers. A total of 1.26 million km of driving data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of heavy commercial vehicles. This dataset provides metadata of recorded tracks as well as high-resolution time series data of the vehicle speed. Its applications include simulation of electrification for heavy commercial vehicles, modeling logistics processes or driving cycle construction.

KW - Fleet data

KW - GNSS

KW - Logistics

KW - Mobility data

KW - Road freight transport

KW - Truck

UR - https://www.scopus.com/pages/publications/85160641821

U2 - 10.1016/j.dib.2023.109246

DO - 10.1016/j.dib.2023.109246

M3 - Article

AN - SCOPUS:85160641821

SN - 2352-3409

VL - 48

JO - Data in Brief

JF - Data in Brief

M1 - 109246

ER -

Heavy commercial vehicles' mobility: Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)

Abstract

Keywords

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