Electrical Vehicle Charging Station Deployment Based on Real World Vehicle Trace

  • Li Yan
  • Haiying ShenEmail author
  • Shengyin Li
  • Yongxi Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10036)


The fast development of smart-grid technologies and applications calls for new means to meet the transportation and environment requirements of the next trend of mainstream vehicles. Electric vehicle (EV), which has been regarded as an important replacement for present gasoline-based vehicle, is expected to greatly reduce the carbon emissions meanwhile offer acceptable transportation ability. However, most of present market-level electric vehicle heavily rely its capacity-constrained battery which can only support limited driving range. Although there have been many pioneer works focusing on ameliorating the driving experience of EVs through tuning the placement of charging infrastructure, most of them do not consider the heterogeneity of vehicle movement in different scenarios. In this paper, starting from a fine-grained analysis of a real-world vehicle trace, a charging station placement algorithm considering the installation cost, traffic flow and battery capacity, called EVReal, is proposed. In comparing its performance with other representative algorithms, EVReal outperforms the others in various metrics.


Charge Station Road Network Electric Vehicle Traffic Flow Power Load 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was supported in part by U.S. NSF grants NSF-1404981, IIS-1354123, CNS-1254006, and Microsoft Research Faculty Fellowship 8300751.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Li Yan
    • 1
  • Haiying Shen
    • 1
    Email author
  • Shengyin Li
    • 2
  • Yongxi Huang
    • 2
  1. 1.University of VirginiaCharlottesvilleUSA
  2. 2.Clemson UniversityClemsonUSA

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