Methods for improving bicycle sharing system balance.

Details

• Creators:
  O'Kelly, Morton E.
• Corporate Creators:
  NEXTRANS Center (U.S.)
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Bicycling
  • Sustainable transportation
  • Optimization
  • Vehicle sharing
  • Bicycle facilities
  • Geographic information systems
  • CoGo
  • Columbus, Ohio
• Resource Type:
  Tech Report
• Geographical Coverage:
  Ohio ; United States
• Corporate Publisher:
  NEXTRANS Center (U.S.)
• Abstract:
  Many cities have developed bicycle sharing systems. This project points out that a key element in their ; success and sustainability is an understanding of the spatial patterns of supply and demand. This project ; tackles the re‐balancing issue where bikes must be removed from full stations and replenished at empty ; ones. Taking inspiration from the lot size problem, and capacitated vehicle routing, the project devises a ; rolling window approach to this problem, in essence representing the amount of foresight that the ; system planner can use to determine solutions. The submitted paper shows that a problem which might ; be unsolvable with a more myopic approach can actually be solved satisfactorily when a longer window ; range is used. The penalty for this added window (look‐ahead) is of course added computational effort ; but the paper shows that this effort is manageable for the relatively small sample system analyzed here ; (Columbus, Ohio). The paper reporting these efforts is in review. The paper is illustrated with results ; from 54 problem instances derived from variants of the base data. The results are derived on a standard ; computer with widely available tools such as Python and CPLEX.
  More +
• Format:
  PDF
• Funding:
  170OSUY2.2
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32312/dot_32312_DS1.pdf
• File Type:
  [PDF - 1.32 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:747c09053b771575d393e7016cc1ca0aedb0eb0142b3d818c7238b78d044b50b