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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.
|Title of host publication||2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2020)|
|Number of pages||5|
|Publication status||Published - 2020|
|Event||2020 IEEE International Conference on Industrial Engineering and Engineering Management - Marina Bay Sands, Singapore, Singapore|
Duration: 14 Dec 2020 → 17 Dec 2020
|Conference||2020 IEEE International Conference on Industrial Engineering and Engineering Management|
|Location||Marina Bay Sands|
|Period||14/12/2020 → 17/12/2020|
- Freight trucks
- GPS data
- Parking measures
- Rest areas
FingerprintDive into the research topics of 'GPS-Derived measures of freight trucks for rest areas: a case-study based analysis'. Together they form a unique fingerprint.
- 1 Finished
”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