At Sam Schwartz, making the journey better begins with identifying and bringing together all the resources at our disposal. At LaGuardia Airport (LGA), ongoing construction and constrained roadways has created a dire traffic congestion issue; recurring gridlock leads to operational challenges and a decreased customer experience. Given record passenger growth and the sudden popularity of rideshare services, measuring and predicting airport roadway congestion in real-time has become more necessary than ever.

The first step towards real-time monitoring is automating collection from dozens of data sources, from roadway sensors to bus location APIs to emailed reports. By consolidating these streams into a single database, Sam Schwartz and LGA’s redevelopment program have been able to identify key metrics for anticipating traffic congestion. This also allows for the easy comparison of historical baselines to current trends, along with the automated creation of daily reports.

To present these daily reports in a useful, engaging manner, the data team at Sam Schwartz built a set of interactive dashboards. The cover page (Fig. 1) provides an overview of the previous day’s conditions, displaying information like alerts, weather, cancellations and delays, and bus travel times. Another page (Fig. 2) dives further into the traffic alert codes and the Port Authority Police Department’s mitigation efforts at the airport. Information previously only accessible as text is now constantly being scraped from Airport Operations Center emails and saved in a database; displaying this data across a week allows for day to day comparisons of traffic conditions and staffing deployments. Hovering a cursor over specific hours also pulls up associated information about each alert or mitigation.

Moving beyond reporting yesterday’s activity, the dashboard now features live pages updated every minute. One page (Fig. 3) displays real-time traffic speeds on the airport’s roadways. By continuously collecting information through a Waze API, a historical average for that day of the week can be calculated (the black line) and compared with speeds on that specific day (the white line).

Another valuable set of metrics concern For-Hire Vehicle activity (Fig. 4). Using the Lyft API, the data team has been able to calculate hourly pickups and drop offs in different locations at LGA, giving insight into the temporal and spatial distribution of passengers as they use app-based transportation services.

Consolidating data streams and displaying operations and trends reveals a clearer view of the pulse of the airport. Instead of monitoring a series of video feeds, the Operations Center can now easily and precisely identify congestion through a top down view, and get accurate vehicle pickup counts from the source itself. By leveraging custom-built visualizations, planning and operations can be supported with an empirical rigor that has been previously unattainable, benefitting both customers and workers as LGA continues to redevelop.

The Sam Schwartz LGA team is: Yana Chudnaya, Matthew Dwyer, Evan Nowak, Ben Rosen-Filardo, Dora Miketa, Alex Spence, Jasie Chou, and Zeke Mermell.

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