Houston METRO operates 42 park-and-ride facilities across the region, serving thousands of trips each day. METRO needed current data on how these lots are used and who uses them, to guide future planning and operations as demand across the network continues to grow.
Foursquare ITP led a comprehensive license plate survey to analyze usage patterns, estimate user demographics, and gather data to support future planning and operational strategies. The team coordinated the survey of nearly 10,000 vehicles across these facilities, including the development of a routing algorithm to plan survey teams’ movements. Based on photographs of surveyed vehicles, the team developed a machine learning process to extract license plate text and queried the Texas Department of Motor Vehicles Motor Vehicle Information database to obtain registration information for the surveyed vehicles. Using these addresses, we performed demographic analyses of lot users, modeled the driving distance to the facility, and compared these alongside transit service levels. We also analyzed lot utilization and ridership to identify trends.
We compiled the findings into a set of facility profiles that METRO uses to understand local ridership trends, develop marketing strategies, inform rideshare/carpooling initiatives and emissions-reduction campaigns, and validate mode-share data and transit demand modeling.
Solutions and Outcomes
- Developed an optimized data collection schedule using GIS Network Analyst to minimize travel time and maximize site coverage.
- Collected over 10,000 license plate counts in partnership with local firms and METRO staff, validating nearly 9,000 results.
- Applied Foursquare ITP’s machine learning toolkit to trace vehicle origin addresses from field photos.
- Delivered facility profiles combining travel time distribution, demographic, and kernel density analyses to support future planning decisions.