GPS-Derived measures of freight trucks for rest areas: a case-study based analysis

Ahmed Karam Abdelfattah Mostafa; Thorbjørn Martens Illemann; Kristian Hegner Reinau

doi:10.1109/IEEM45057.2020.9309748

GPS-Derived measures of freight trucks for rest areas: a case-study based analysis

Ahmed Karam Abdelfattah Mostafa, Thorbjørn Martens Illemann, Kristian Hegner Reinau

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

2 Citationer (Scopus)

Abstract

Comprehensive knowledge on how freight trucks utilize rest areas along motorways is essential to prioritize effectively which rest areas need expansion and to decide on where to add new rest areas. Private logistics companies daily archive a large amount of GPS data from trucks that can provide knowledge on the usage patterns of rest areas. This paper presents a methodology to collect and process GPS data from logistics companies to aid public authorities in planning road infrastructures. The developed methodology combines a database management system implemented by PostgreSQL with PostGIS and a MATLAB code. The database system is used to collect and store the GPS data from logistics companies. The MATLAB code implements a systematic procedure to process the GPS data and extract parking statistics, such as average length of truck stay, number of parked trucks, and spatial analyses of the parked truck locations. The methodology is applied to a rest area using GPS data from two large Danish logistics companies. The results show the potentials of GPS truck data to understand the truck parking patterns.

Originalsprog	Engelsk
Titel	2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020)
Antal sider	5
Forlag	IEEE
Publikationsdato	2020
Sider	939-943
Artikelnummer	9309748
ISBN (Trykt)	978-1-5386-7221-1
ISBN (Elektronisk)	978-1-5386-7220-4
DOI	https://doi.org/10.1109/IEEM45057.2020.9309748
Status	Udgivet - 2020
Begivenhed	2020 IEEE International Conference on Industrial Engineering and Engineering Management - Marina Bay Sands, Singapore, Singapore Varighed: 14 dec. 2020 → 17 dec. 2020 http://www.ieem.org/public.asp?page=index.asp

Konference

Konference	2020 IEEE International Conference on Industrial Engineering and Engineering Management
Lokation	Marina Bay Sands
Land/Område	Singapore
By	Singapore
Periode	14/12/2020 → 17/12/2020
Internetadresse	http://www.ieem.org/public.asp?page=index.asp

Adgang til dokumentet

10.1109/IEEM45057.2020.9309748

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

Andre filer og links

Link to publication in Scopus

”A New System for Sharing Data Between Logistics Companies and Public Infrastructure Authorities: Improving Infrastructure While Maintaining Competitive Advantage”
Reinau, K. H., Luan, J., Illemann, T. M., Karam, A. & Stakenaite, D.
01/12/2018 → 30/03/2021
Projekter: Projekt › Forskning

Citationsformater

@inproceedings{16fe6a9b2a5e4deb8c4944474d846ed3,

title = "GPS-Derived measures of freight trucks for rest areas: a case-study based analysis",

abstract = "Comprehensive knowledge on how freight trucks utilize rest areas along motorways is essential to prioritize effectively which rest areas need expansion and to decide on where to add new rest areas. Private logistics companies daily archive a large amount of GPS data from trucks that can provide knowledge on the usage patterns of rest areas. This paper presents a methodology to collect and process GPS data from logistics companies to aid public authorities in planning road infrastructures. The developed methodology combines a database management system implemented by PostgreSQL with PostGIS and a MATLAB code. The database system is used to collect and store the GPS data from logistics companies. The MATLAB code implements a systematic procedure to process the GPS data and extract parking statistics, such as average length of truck stay, number of parked trucks, and spatial analyses of the parked truck locations. The methodology is applied to a rest area using GPS data from two large Danish logistics companies. The results show the potentials of GPS truck data to understand the truck parking patterns. ",

keywords = "Freight trucks, GPS data, Parking measures, Rest areas",

author = "Mostafa, {Ahmed Karam Abdelfattah} and Illemann, {Thorbj{\o}rn Martens} and Reinau, {Kristian Hegner}",

year = "2020",

doi = "10.1109/IEEM45057.2020.9309748",

language = "English",

isbn = "978-1-5386-7221-1",

pages = "939--943",

booktitle = "2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020)",

publisher = "IEEE",

address = "United States",

note = "2020 IEEE International Conference on Industrial Engineering and Engineering Management ; Conference date: 14-12-2020 Through 17-12-2020",

url = "http://www.ieem.org/public.asp?page=index.asp",

}

Mostafa, AKA, Illemann, TM & Reinau, KH 2020, GPS-Derived measures of freight trucks for rest areas: a case-study based analysis. i 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020) ., 9309748, IEEE, s. 939-943, 2020 IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, Singapore, 14/12/2020. https://doi.org/10.1109/IEEM45057.2020.9309748

GPS-Derived measures of freight trucks for rest areas: a case-study based analysis. / Mostafa, Ahmed Karam Abdelfattah; Illemann, Thorbjørn Martens; Reinau, Kristian Hegner.
2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020) . IEEE, 2020. s. 939-943 9309748.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - GPS-Derived measures of freight trucks for rest areas: a case-study based analysis

AU - Mostafa, Ahmed Karam Abdelfattah

AU - Illemann, Thorbjørn Martens

AU - Reinau, Kristian Hegner

PY - 2020

Y1 - 2020

N2 - Comprehensive knowledge on how freight trucks utilize rest areas along motorways is essential to prioritize effectively which rest areas need expansion and to decide on where to add new rest areas. Private logistics companies daily archive a large amount of GPS data from trucks that can provide knowledge on the usage patterns of rest areas. This paper presents a methodology to collect and process GPS data from logistics companies to aid public authorities in planning road infrastructures. The developed methodology combines a database management system implemented by PostgreSQL with PostGIS and a MATLAB code. The database system is used to collect and store the GPS data from logistics companies. The MATLAB code implements a systematic procedure to process the GPS data and extract parking statistics, such as average length of truck stay, number of parked trucks, and spatial analyses of the parked truck locations. The methodology is applied to a rest area using GPS data from two large Danish logistics companies. The results show the potentials of GPS truck data to understand the truck parking patterns.

AB - Comprehensive knowledge on how freight trucks utilize rest areas along motorways is essential to prioritize effectively which rest areas need expansion and to decide on where to add new rest areas. Private logistics companies daily archive a large amount of GPS data from trucks that can provide knowledge on the usage patterns of rest areas. This paper presents a methodology to collect and process GPS data from logistics companies to aid public authorities in planning road infrastructures. The developed methodology combines a database management system implemented by PostgreSQL with PostGIS and a MATLAB code. The database system is used to collect and store the GPS data from logistics companies. The MATLAB code implements a systematic procedure to process the GPS data and extract parking statistics, such as average length of truck stay, number of parked trucks, and spatial analyses of the parked truck locations. The methodology is applied to a rest area using GPS data from two large Danish logistics companies. The results show the potentials of GPS truck data to understand the truck parking patterns.

KW - Freight trucks

KW - GPS data

KW - Parking measures

KW - Rest areas

UR - http://www.scopus.com/inward/record.url?scp=85099752926&partnerID=8YFLogxK

U2 - 10.1109/IEEM45057.2020.9309748

DO - 10.1109/IEEM45057.2020.9309748

M3 - Article in proceeding

SN - 978-1-5386-7221-1

SP - 939

EP - 943

BT - 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020)

PB - IEEE

T2 - 2020 IEEE International Conference on Industrial Engineering and Engineering Management

Y2 - 14 December 2020 through 17 December 2020

ER -

GPS-Derived measures of freight trucks for rest areas: a case-study based analysis

Abstract

Konference

Adgang til dokumentet

AUB Link

Andre filer og links

Fingeraftryk

Projekter

”A New System for Sharing Data Between Logistics Companies and Public Infrastructure Authorities: Improving Infrastructure While Maintaining Competitive Advantage”

Citationsformater