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Fuel-Saving Potentials of Platooning Evaluated through Sparse Heavy-Duty Vehicle Position Data
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. Scania CV AB, Sweden.ORCID-id: 0000-0001-5107-2942
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.ORCID-id: 0000-0002-3672-5316
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.ORCID-id: 0000-0001-9940-5929
2014 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Vehicle platooning is important for heavy-duty vehicle manufacturers, due to the reduced aerodynamic drag for the follower vehicles, which gives an overall lower fuel consumption. Heavy-duty vehicle drivers are aware this fact and sometimes drive close to other heavy-duty vehicles. However, it is not currently well known how many vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-duty vehicles by analyzing sparse vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2014. s. 1061-1068
Emneord [en]
Fuel economy, Image matching, Inference engines, Intelligent vehicle highway systems, Vehicles
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-159049DOI: 10.1109/IVS.2014.6856540ISI: 000346153100169Scopus ID: 2-s2.0-84905394246ISBN: 978-147993638-0 (tryckt)OAI: oai:DiVA.org:kth-159049DiVA, id: diva2:782989
Konferanse
IEEE Intelligent Vehicles Symposium (IV), JUN 08-11, 2014, Dearborn, MI, USA
Merknad

QC 20150123

Tilgjengelig fra: 2015-01-23 Laget: 2015-01-20 Sist oppdatert: 2022-06-23bibliografisk kontrollert

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