Smart Rideshare Matching – Feasibility of Utilizing Personalized Preferences

Current transport-share systems or carpooling typically rely on users to actively request or offer a ride and to coordinate the time and pickup location. Services such as Lyft and Uber have addressed this problem by using location to provide ride services that are convenient and on-demand. The on-demand and convenience aspects of transportation might also be the main reason behind using personal cars as they allow to combine commutes with other activities (e.g., picking up kids to and from school, running errands, going to off-campus meetings, etc.). This convenience, however, comes at a great personal and societal cost including traffic congestion, parking demand, stress, and health problems. Despite various agencies' incentives and discounts for ridesharing, this kind of service has not been widely used for obvious reasons mentioned above as well as hassled coordination, scheduling requirements, commitment, and having to actively request or offer rides. In this project, the research team proposes to conduct a case study using a university community to increase engagement in ridesharing in the UVA community by building a proactive context-aware matching and recommendation system that matches the community members based on predicted ride events inferred from their calendars and routines (e.g., shared time and location of events in Outlook calendar).

Language

• English

Project

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

  69A3552348303

• Sponsor Organizations:

  Sustainable Mobility and Accessibility Regional Transportation Equity Research Center

  Morgan State University
  Baltimore, MD  United States 

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Project Managers:

  Niehaus, Joseph

• Principal Investigators:

  Park, Brian

  Chen, Donna

  Doryab, Afsaneh

  Mondschein, Andrew

• Start Date: 20230901
• Expected Completion Date: 20240901
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Consumer preferences; Recommendations; Ridesharing
• Subject Areas: Data and Information Technology; Passenger Transportation; Public Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 01893884
• Record Type: Research project
• Source Agency: Sustainable Mobility and Accessibility Regional Transportation Equity Research Center
• Contract Numbers: 69A3552348303
• Files: UTC, RIP
• Created Date: Sep 21 2023 3:48PM