Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Look-ahead speed planning for heavy-duty vehicle platoons using traffic information
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0003-2654-8173
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0002-1375-9054
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
Scania AB.
2017 (English)In: Transportation Research Procedia, ISSN 2324-9935, E-ISSN 2352-1465, Vol. 22, p. 561-569Article in journal (Refereed) Published
Abstract [en]

Freight transport is a fast increasing transportation mode due to the economic growth in the world. Heavy-duty vehicles (HDV) have considerably greater fuel consumption, thus making them a suitable target when new policies in road transport emphasize increased energy efficiency and mitigated emission impacts. Intelligent transportation systems, based on emerging V2X communication technology, open new possibilities for developing fuel-efficient driving support functions considering real traffic information. This indicates a large potential of fuel saving and emission reduction for freight transport. This paper studies a dynamic programming-based optimal speed planning considering a maximum acceleration model for HDVs. The optimal speed control is applied for the deceleration case of HDV platoons due to received information on traffic speed reduction ahead. The control can optimize fuel consumption as well as travel time, and theoretical results for the two cases are presented. For maximal fuel saving, a microscopic traffic simulation study is performed for single HDVs and HDV platoons running in real traffic conditions. The results show a decrease in fuel consumption of more than 80% compared to simulations without applying optimal control, while the fuel consumption of other vehicles in the simulation is not significantly affected.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 22, p. 561-569
National Category
Transport Systems and Logistics Control Engineering
Research subject
Transport Science; Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-210173DOI: 10.1016/j.trpro.2017.03.045Scopus ID: 2-s2.0-85019435576OAI: oai:DiVA.org:kth-210173DiVA, id: diva2:1117167
Note

QC 20170628

Available from: 2017-06-28 Created: 2017-06-28 Last updated: 2018-05-16Bibliographically approved
In thesis
1. Simulation Studies of Impact of Heavy-Duty Vehicle Platoons on Road Traffic and Fuel Consumption
Open this publication in new window or tab >>Simulation Studies of Impact of Heavy-Duty Vehicle Platoons on Road Traffic and Fuel Consumption
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The demand for road freight transport continues to grow with the growing economy, resulting in increased fossil fuel consumption and emissions. At the same time, the fossil fuel use needs to decrease substantially to counteract the ongoing global warming. One way to reduce fuel consumption is to utilize emerging intelligent transport system (ITS) technologies and introduce heavy-duty vehicle (HDV) platooning, i.e. HDVs driving with small inter-vehicle gaps enabled by the use of sensors and controllers. It is of importance for transport authorities and industries to investigate the effects of introducing HDV platooning. Previous studies have investigated the potential benefits, but the effects in real traffic, both for the platoons and for the surrounding vehicles, have barely been explored. To further utilize ITS and optimize the platoons, information about the traffic situation ahead can be used to optimize the vehicle trajectories for the platoons. Paper I presents a dynamic programming-based optimal speed control including information of the traffic situation ahead. The optimal control is applied to HDV platoons in a deceleration case and the potential fuel consumption reduction is evaluated by a microscopic traffic simulation study with HDV platoons driving in real traffic conditions. The effects for the surrounding traffic are also analysed. Paper II and Paper III present a simulation platform to assess the effects of HDV platooning in real traffic conditions. Through simulation studies, the potential fuel consumption reduction by adopting HDV platooning on a real highway stretch is evaluated, and the effects for the other vehicles in the network are investigated.

Abstract [sv]

Efterfrågan på godstransporter på väg fortsätter att öka i takt med den växande ekonomin, vilket resulterar i ökad förbrukning av fossila bränslen och ökade utsläpp. Samtidigt behöver användandet av fossila bränslen minska för att motverka den pågående globala uppvärmningen. Ett sätt för att minska bränsleförbrukningen är att utnyttja den teknik kring intelligenta transportsystem som är under utveckling och introducera lastbilskonvojer, det vill säga lastbilar som använder sensorer och regulatorer för att kunna köra med korta avstånd mellan sig. För transportföretag och -myndigheter är det viktigt att undersöka effekterna av att införa lastbilskonvojkörning. Tidigare studier har undersökt de möjliga fördelarna, men effekterna vid körning i trafik, både för konvojerna och för omgivande fordon, är outforskade. För att ytterligare utnyttja intelligenta transportsystem och optimera konvojerna kan information om trafiksituationen längre fram på vägen användas för att optimera konvojernas körning. Artikel I presenterar en optimal hastighetsregulator baserad på dynamisk programmering och som inkluderar information om trafiksituationen längre fram. Den optimala regulatorn appliceras på lastbilskonvojer under ett inbromsningsscenario och den potentiella minskningen i bränsleförbrukning utvärderas genom en mikroskopisk trafiksimuleringsstudie där lastbilskonvojerna kör i verkliga trafikförhållanden. Effekterna för omgivande fordon är också analyserade.Artikel II och artikel III presenterar en simuleringsplattform för att utvärdera effekterna av lastbilskonvojkörning i verkliga trafikförhållanden. Genom simuleringsstudier analyseras den potentiella bränsleförbrukningsminskningen då lastbilskonvojer körs på en verklig motorvägssträcka och effekterna för de övriga fordonen på vägen undersöks.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 26
Series
TRITA-ABE-DLT ; 1813
Keyword
heavy-duty vehicle platooning, microscopic traffic simulation, intelligent transport systems, optimal control, longitudinal cruise control, fuel economy
National Category
Transport Systems and Logistics
Research subject
Transport Science
Identifiers
urn:nbn:se:kth:diva-227996 (URN)978-91-7729-777-2 (ISBN)
Presentation
2018-06-13, Nash/Wardrop, Teknikringen 10, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
VINNOVA, 2014-06200J. Gust. Richert stiftelse, 2016-00295
Note

QC 20180516

Available from: 2018-05-16 Created: 2018-05-16 Last updated: 2018-05-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Johansson, IngridJin, JunchenMa, Xiaoliang
By organisation
Transport Planning, Economics and Engineering
In the same journal
Transportation Research Procedia
Transport Systems and LogisticsControl Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 66 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf