What are some metrics of performance related to the supply and operation of municipal parking in Hamilton?
Project Description:
Public parking is going through a period of significant change. Traditional parking locations are being repurposed for development or the public realm (cycling & pedestrian facilities, trees, restaurant patios, etc.) while new technologies are creating unrealized opportunities. The City of Hamilton manages over 4000 public parking spaces and is incorporating connected technologies to improve operational efficiency but not the user experience. Currently live data is being produced for every transaction in public surface lots through pay by plate technology. Moving forward this will be expanded to every paid parking space operated by the City using a variety of systems. Parking payment transactions are not an exact indicator of parking occupancy, with many payments exceeding the time used while some are insufficient, however there is a correlation between payments and utilization. The City would like to harness the data being produced to benefit the user, particularly as public parking becomes less visible and harder to find.
Challenge Summary:
Students will mine through the various data sets supplied by the City to determine what applicable findings can be researched to inform policies and guidelines related to the supply and operation of City-supplied parking within the City of Hamilton.
Deliverables: Feasibility study, presentation
Where the work will go and what it will be used for:
It is intended that this study will inform the City on how to enhance their data repository by identifying any new useful data to collect within their existing data-collection processes and capabilities, and any long-term investments required to further enhance data collection to better-inform policy decisions related to the supply and operation of municipal parking.
City Staff: Julianna Petrovich, Project Manager, New Initiatives, Transportation Planning & Parking, City of Hamilton
Faculty, Course & Students: Analytics Competition (student data analytics competition) with Mohawk College instructor Steven Way
