Dynamic Routing for Ridesharing

The transportation sector represents a major part in the current and future US economy, with more than 10% of the United States’ GDP directly related to transportation activity. The significant congestion and projected demand increases with limited infrastructure investment make necessary the development of significant improvement on transportation systems. Transportation planners must therefore find ways to improve transportation conditions in a cost-efficient manner. Significant advances have been made in the procurement and provision of real-time information that would be required for the effective control of a transportation system. Yet, this information is mostly used in a centralized transit system design and operation. These efforts have had limited success to date addressing congestion in most American cities, which have a dispersed demand due to a lack of single high-density business and residential centers. Congestion in the US continues to rise, stressing vital infrastructure, causing delayed shipments, late employees, and countless other problems. Although these new mobility options such as ride-sharing are not the complete answer to congestion nationwide, their ability to augment existing public infrastructure, such as mass transit, could help to solve many congestion related problems in urban areas like Los Angeles. This research will develop new dynamic routing models and algorithms to support the special features of ridesharing such as High Occupancy Vehicles (HOVs) lanes and based on the developed models and algorithms, the research team will study the impact of these lanes on facilitating ridesharing. Traffic congestion is a significant social concern that is credited with considerable economic costs, wasted time, and associated public health risks. Efficient ridesharing solutions could help mitigate congestion. However, given a fleet of vehicles and ridesharing passenger requests, finding efficient ridesharing routes should take into account existing policies of discounted toll rates on High Occupancy Toll (HOT) lanes and the availability of HOV lanes, which could provide cost reductions and time savings under congestion. While there is a rich history of using optimization models to determine vehicles routes, the special features that could facilitate ridesharing such as the use of special links in the roadway, namely, the increasing use of High Occupancy Vehicle (HOV) lanes and reduced toll rates for high occupancy vehicles on many roads and bridges makes the nature of the routing solution different from other routing problems. In most routing problems the addition of an extra pickup request will usually increase the objective function (e.g., travel time) but in the ridesharing context the objective function could be reduced with the extra pickup due to being able to qualify for a HOV lane. Thus, the objective of this research is to develop dynamic routing algorithms to support ridesharing.

Language

  • English

Project

  • Status: Programmed
  • Funding: $100000
  • Contract Numbers:

    DOT 69A3551747114

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590

    National Center for Sustainable Transportation

    University of California, Davis
    Davis, CA  United States 
  • Managing Organizations:

    National Center for Sustainable Transportation

    University of California, Davis
    Davis, CA  United States 

    METRANS Transportation Center

    University of Southern California
    Los Angeles, CA  United States  90089-0626
  • Project Managers:

    Iacobucci, Lauren

  • Performing Organizations:

    National Center for Sustainable Transportation

    University of California, Davis
    Davis, CA  United States 

    METRANS Transportation Center

    University of Southern California
    Los Angeles, CA  United States  90089-0626
  • Principal Investigators:

    Dessouky, Maged

  • Start Date: 20200816
  • Expected Completion Date: 20210815
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01739757
  • Record Type: Research project
  • Source Agency: National Center for Sustainable Transportation
  • Contract Numbers: DOT 69A3551747114
  • Files: UTC, RiP
  • Created Date: May 22 2020 1:45PM