On the computation of the energy-optimal route dependent on the traffic load in Ingolstadt

In this paper, the authors evaluate energy-optimal paths in the road network of Ingolstadt. The energy consumption associated with the segments of the road network are derived from the measurements of the traffic load based on vehicle probe data, using a mesoscopic traffic model and a physical vehicle consumption model. The resulting description of the network is time-dependent, thereby reproducing the variations in time of the traffic load in Ingolstadt. The results suggest that the average energy consumption associated with energy-optimal paths is approximately 10% lower than the average energy consumption associated with fast paths. Moreover, they find that energy-optimal paths differ from fast paths in more than 90% of the considered test cases and that the density of junctions has a strong impact on the average energy consumption. Although the time dependency of the network description leads to an increase in the computation time of optimal paths, the query times of one of the evaluated methods are promising for practical applications.

• Record URL:
  • https://doi.org/10.1016/j.trc.2013.07.001
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0968090X1300137X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Kluge, S
  • Santa, C
  • Dangl, S
  • Wild, S
  • Brokate, M
  • Reif, K
  • Busch, F
• Publication Date: 2013-11

Language

• English

Media Info

• Media Type: Print
• Features: Figures; Maps; References; Tables;
• Pagination: pp 97-115
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 36
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Electric vehicles; Energy conservation; Energy consumption; Mesoscopic traffic flow; Routes; Shortest path algorithms; Time dependence; Traffic density
• Uncontrolled Terms: Road networks
• Geographic Terms: Ingolstadt (Germany)
• Subject Areas: Energy; Highways; Planning and Forecasting; I15: Environment; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01501443
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 19 2013 9:00AM