City-scalable Destination Recommender System for On-demand Senior Mobility

As one of the direct beneficiaries of advances in information & communications technologies, mobility on-demand (MOD) fleet operations have grown increasingly relevant to the operation of smart cities. Many seniors face mobility issues and differences in life-style from the rest of the population; as a result, recommended destinations for the general population may not be preferable to this specific subpopulation. This project is developing a new inference tool that fleet operators can use over time to efficiently learn users’ preferences for different destinations. A “routing-constrained recommender system” is being developed with a component to select a subset of destinations that are route-constrained to recommend to the user to select, and sequential learning component that takes different users’ feedback (e.g. a 5-star rating and selection of destination in each case) to update the knowledge base.

• Record URL:
  http://c2smart.engineering.nyu.edu/current-projectscity-scalable-destination-recommender-system-for-on-demand-senior-mobility/

Language

• English

Project

• Status: Active
• Funding: $124155
• 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:

  Connected Cities for Smart Mobility towards Accessible and Resilient Transportation

  New York University
  New York, NY  United States  10031
• Performing Organizations:

  Connected Cities for Smart Mobility towards Accessible and Resilient Transportation

  New York University
  New York, NY  United States  10031
• Principal Investigators:

  Chow, Joseph

  Cheu, Ruey

• Start Date: 20170301
• Expected Completion Date: 20180630
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Aged; Algorithms; Consumer preferences; Demand responsive transportation; Mobility; Recommendations; Routes and routing
• Subject Areas: Data and Information Technology; Planning and Forecasting; Public Transportation; Society;

Filing Info

• Accession Number: 01648397
• Record Type: Research project
• Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation
• Files: UTC, RiP
• Created Date: Oct 12 2017 10:11AM