Shared work fleets with on-demand logistics - ON-177

Preferred Disciplines: Machine Learning, Predictive Analytics, Modelling (Masters or PhD)
Company: Anonymous
Project Length: 4-6 months (1 unit)
Desired start date: As soon as possible
Location: Waterloo, ON
No. of Positions: 1
Preferences: Southeastern Ontario Universities (Toronto, Hamilton, Waterloo, London)

About the Company: 

We are a one-stop shop solution to transition to shared work fleet vehicles.  We provide the needed software, hardware, consulting and support services.  We are currently working with university fleets to meet their needs.

Project Description:

We are currently working on creating a system of “Uber for fleet vehicles” helping to coordinate vehicle movement as well as coordinating shared equipment and supplies (ladders, tools, etc.)

We are interested in using machine learning algorithms to create a simulation program that can use data on pick-up/drop-off locations, and requests for assets/supplies and recommends:

  1. Where vehicles should go based on that data when not on trips to minimize wait-times
  2. What assets and supplies should be in which vehicles, considering cost and space constraints, to keep costs affordable while getting people, assets and supplies where they need to be as quickly as possible.

Research Objectives:

  • Develop simulation using machine learning to predict pick up and drop off locations
  • Determine best vehicle paths to minimize wait times
  • Determine which assests should be in the vehicle

Methodology:

  • To be determined

Expertise and Skills Needed:

  • AI/Machine Learning
  • Mapping
  • Cost-benefit analyses
  • Predictive analytics

For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects
  2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform.
Program: