Congestion Mitigation Potential of Autonomous (Driverless) Vehicles: a Scenario- Based Approach

Optimization of on-demand transportation systems and ride-sharing services involves solving complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). The authors first propose a time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles’ carrying states within space-time transportation networks, to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested transportation networks. The authors' 3-dimensional state-space-time network model enables comprehensive enumeration of possible transportation states at any given time along vehicle space-time paths, and further allows a forward dynamic programming solution algorithm to solve the single vehicle VRPPDTW problem. Using a Lagrangian relaxation approach, the primal multi-vehicle routing problem is decomposed to a sequence of single vehicle routing sub-problems, with Lagrangian multipliers for individual passengers’ requests being updated by sub-gradient-based algorithms. The authors further discuss a number of search space reduction strategies and test the algorithms, implemented through a specialized program in C++, on medium-scale and large-scale transportation networks, namely the Chicago sketch and Phoenix regional networks.

• 
• Summary URL:
  https://mti.umd.edu/ntc/research/ntc2014-su-r-03-congestion-mitigation-potential-autonomous-driverless-vehicles-scenario-based
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Office of the Assistant Secretary for Research and Technology

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

  Arizona State University, Tempe

  School of Sustainable Engineering and the Built Environment
  Tempe, AZ  United States  85287-5306

  National Transportation Center at Maryland

  1124 Glenn Martin Hall
  University of Maryland
  College Park, MD  United States  20742
• Authors:
  • Zhou, Xuesong
  • Mahmoudi, Monirehalsadat
  • Pendyala, Ram
  • Jalali, Hossein
• Publication Date: 2015-7

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; References; Tables;
• Pagination: 43p

Subject/Index Terms

• TRT Terms: Congestion management systems; Connected vehicles; Demand responsive transportation; Passenger handling; Ridesharing; Routing
• Identifier Terms: C++ (Programming language)
• Geographic Terms: Chicago Metropolitan Area; Phoenix Metropolitan Area
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Passenger Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01667568
• Record Type: Publication
• Report/Paper Numbers: NTC2014-SU-R-03
• Files: UTC, TRIS, ATRI, USDOT
• Created Date: Apr 27 2018 12:23PM