Demand-Driven Operational Design for Shared Mobility with Ride-pooling Options

This proposal aims to develop a demand-driven approach for shared mobility operations with machine learning and math programming methods. The objective of this approach is to incorporate economic, environment and equity impacts over an entire operational cycle. Both ride-hailing systems (e.g. Lyft) and ride-pooling systems (e.g. UberPool) will be investigated. The developed models will be tested with real-world taxi data including detailed trajectories of vehicles and their loading states at all times.

Language

  • English

Project

  • Status: Active
  • Funding: $98718
  • Contract Numbers:

    69A3551747119

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    USDOT/OST-R

    Washington DC,   United States 
  • Project Managers:

    Kline, Robin

  • Performing Organizations:

    Center for Transportation, Environment, and Community Health

    Cornell University
    Ithaca, NY  United States  14853

    University of South Florida, Tampa

    Department of Civil and Environmental Engineering
    4202 E. Flowler Avenue, ENB 118
    Tampa, FL  United States  33620-5350
  • Principal Investigators:

    Samaranayake, Samitha

    Li, Xiaopeng

  • Start Date: 20181001
  • Expected Completion Date: 20190930
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01680346
  • Record Type: Research project
  • Source Agency: Center for Transportation, Environment, and Community Health
  • Contract Numbers: 69A3551747119
  • Files: UTC, RiP
  • Created Date: Sep 13 2018 4:04PM