Predictive Analytics for No-Shows and Cancellations for Paratransit Operations

No-shows and late cancellations waste paratransit operators’ resources, as well as degrade a system’s productivity by preventing other users from utilizing supplied service slots. The objective of this research project is threefold: (i) to develop a classification methodology to predict no-shows and cancellations of trips in paratransit systems, (ii) to incorporate the classification model predictions into trip booking and routing models for paratransit operations (including novel overbooking problems in the context of paratransit), and (iii) to evaluate the value of the classification models’ predictions in paratransit planning and operations. As part of this project, the researchers will collaborate with Puerto Rico’s Metropolitan Bus Authority to develop and apply the data analytic techniques proposed in the project using data from the LV paratransit system previously discussed.

• Record URL:
  https://www.buffalo.edu/transinfo/Research/transportation-operations/ParatransitOperations.html

Language

• English

Project

• Status: Active
• Funding: $150000
• Contract Numbers:

  DTRT13-G-UTC48

• Sponsor Organizations:

  University of Puerto Rico at Mayaguez

  259, Avenida Alfonso Valdés Cobián, ,
  Mayagüez, Puerto Rico  United States  00681

  State University of New York, Buffalo

  212 Ketter Hall
  Buffalo, NY  United States  14260

  Office of the Assistant Secretary for Research and Technology

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

  Office of the Assistant Secretary for Research and Technology

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

  Kang, Jee

  Rodriguez, Daniel

• Performing Organizations:

  Transportation Informatics University Transportation Center

  State University of New York, Buffalo
  Buffalo, NY  United States  14260
• Principal Investigators:

  Kang, Jee Eun

  Rodriguez, Daniel

• Start Date: 20170901
• Expected Completion Date: 20180831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Classification; Data analysis; Mathematical prediction; Operations; Overbooking; Paratransit services; Productivity; Reservations; Routing
• Geographic Terms: Puerto Rico
• Subject Areas: Operations and Traffic Management; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01652083
• Record Type: Research project
• Source Agency: Transportation Informatics University Transportation Center
• Contract Numbers: DTRT13-G-UTC48
• Files: UTC, RIP
• Created Date: Nov 27 2017 1:38PM