Electric Vehicle Sharing Planning and Operations

Details

• Creators:
  Zhao, Dongfang ; Li, Xiaopeng ; Zhang, Yu
• Corporate Creators:
  University of South Florida. Department of Civil and Environmental Engineering
• Corporate Contributors:
  United States. Department of Transportation
• Subject/TRT Terms:
  • Electric vehicles
  • Vehicle sharing
  • Monte Carlo method
  • Traffic simulation
  • Traffic models Shared mobility
  • Car sharing
  • Transportation system planning
  • Transportation system operation and
  • management
• Resource Type:
  Tech Report
• Geographical Coverage:
  Florida;United States
• Corporate Publisher:
  University of South Florida. Center for Transportation, Environment, and Community Health
• Description:
  Dongfang Zhao (ORCID ID 0000-0002-5424-9915); Xiaopeng (Shaw) Li (ORCID ID 0000-0002-5264-3775); Yu Zhang (ORCID ID 0000-0003-1202-626X)
  
  This project includes literature review and proposing a model for EV planning and operations. We first conducted a literature review on the relevant EV planning and operations. Then we propose a model that integrates both electric vehicle technologies and car sharing operations. Based on the simulation model, a dynamic and time-continuous optimization model seeking the optimal design of charging station location and electric vehicle deployment is developed. By discretizing the model, we proposed a Monte Carlo simulation model to evaluate the total system cost for a given location and vehicle deployment design. A heuristic algorithm is developed to solve the optimal system design of station location and vehicle deployment. A numerical test in Yantai city, China is conducted to illustrate the effectiveness of the proposed model and draw managerial insights into how the key parameters affect the optimal system design.
• Format:
  PDF
• Funding:
  69A3551747119
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/35669/dot_35669_DS1.pdf
• File Type:
  [PDF - 853.47 KB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:0a82d1d999b555163a76c484431fb7ad655dab3e478189162572beaae7411db27313078dc43546e722dfc56a1391b5d18504ee6711c9939f86d7721db927de82