Digital Infrastructure Solves Chronic Airport Congestion

With the holiday season quickly approaching, we know one thing to be true: airports will be unbearably busy. It’s no surprise major U.S. airports are consistently ranked as the world’s busiest, and those top rankings come at a price—both to travelers and the environment. Chronic problems like traffic congestion and vehicle emissions are suffocating in these bustling hubs. 

 

To address these issues on the landside, airport authorities have spent billions, primarily on capital projects to improve passenger vehicle access—but these have, unfortunately, generated minimal results. 

Lacuna believes there’s a more substantial and sustainable way—dynamic curb management through the use of digital infrastructure. Leveraging digital infrastructure with data from an airport’s current physical infrastructure, and working in partnership with rideshare/taxi operators, dynamic curb management can prioritize more sustainable modes like electric vehicles, as one example. 

Our recent work published in Transport Findings, demonstrates we’re on to something. This peer-reviewed study demonstrates the impact of real-time digital transportation policy at a major U.S. airport, for the first time.  Authored alongside experts from the Pacific Northwest National Laboratory, our study was part of the "Dynamic Curbs in Urban Settings Project" funded by the U.S. Department of Energy Grant, created to analyze how dynamic curb allocation impacts traveler time, congestion and emissions. 

Officials at Seattle-Tacoma International Airport (SEA) have long sought to address the ground traffic congestion causing significant delays for passengers. One of the methods they employed was implementing variable messaging signboards (VMS) to divert traffic between arrivals and departures during times of congestion. However, they weren’t sure if the signage or their interventions were helping, or how to optimize their use. 

SEA asked our research team to investigate. We used real-time sensor data to measure traffic flow and assess congestion at SEA to understand if drivers were adhering to messaging signs, and then evaluated how useful these signs were at impacting congestion in terms of saving traveler time. 

 

Airport flow

 

We found when the airport utilized these messaging signs to improve congestion—it was effective: between 5.5 and 9.1% of drivers diverted from departures to arrivals when the sign read “departures full, use arrivals”, and conversely, between 1.9 and 4.2% of drivers diverted from arrivals to departures.

Further, we found if airports use their existing infrastructure more smartly, they might be able to reduce congestion in the airport by 300% at peak times (this finding is part of a separate, follow-on study that is currently awaiting peer review).

What This Means 

Quantifying the effect of a dynamic intervention, like messaging boards, in a robust, reproducible, and interpretable manner is a crucial step towards implementing closed looped policy that can optimize for the objectives airports care about. It underscores how effective digital infrastructure can be in addressing chronic transportation problems like congestion and pollution—and how this can have a significant impact on future capital budgeting (the cost of concrete vs. the cost of digital infrastructure).

A dollar invested in physical infrastructure is finite—that road or sidewalk can benefit a single community or airport for a limited amount of time. But a dollar invested in digital infrastructure is infinite—we can see more, do more, and more effectively manage the public right-of-way to ensure efficiency and sustainability. 

We’re proud to partner with SEA, a thought leader among airports, on this work. Get in touch with us if you’d like to learn more about digital infrastructure, dynamic curb management and digital policy - we believe it’s transportation’s path to a safer, cleaner, more equitable and efficient future.


Shushman Choudhury, Lead Research Scientist

Shushman Choudhury is Lacuna’s Lead Research Scientist and specializes in Artificial Intelligence techniques for real-time digital policy. He has a Ph.D. in Computer Science from Stanford University, where he developed optimization and decision-making algorithms for intelligent transportation systems. He also has an MS in Robotics from Carnegie Mellon University.

https://www.linkedin.com/in/shushman-choudhury-b29049139/
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