In January, we had the opportunity to present our research at the Transportation Research Board (TRB) Annual Meeting as part of the poster session for the 2025 INRIX x MetroLab Challenge.
The 2025 INRIX x MetroLab Challenge is a partnership that brings together students, researchers, government leaders, and transportation experts to highlight how data-driven analysis can be translated into actionable insights for improving urban mobility and public decision-making. Representing the NYU C2SMART Center and the Transportation Systems program, our team was honored to be among the 2025 winning teams selected to showcase how high-resolution INRIX data can inform real-world transportation policy.
Studying Congestion Pricing at a Critical Moment
On January 5, 2025, New York City launched its congestion pricing program, establishing a Congestion Relief Zone (CRZ) below 60th Street in Manhattan with tolls that vary by vehicle type and time of day. This policy created a rare and timely opportunity to quantify how different drivers adapt to pricing and to better understand the policy’s effectiveness. Our analysis revealed notable heterogeneity in driver responses across vehicle types. We were particularly interested in whether different vehicle classes responded differently and what those differences might imply for policy effectiveness.
Leveraging INRIX Data and Confronting Real-World Challenges
The foundation of our analysis was INRIX Trips Data. This data provided high granularity, specifically the Origin-Destination (O-D) coordinates, timestamps, and vehicle weight classifications. This dataset enabled us to go beyond simple traffic volume counts.
One challenge that we faced was the temporal inconsistency in data sampling rates (sample bias) between the 2024 and 2025 datasets. Differences in the probe sources/penetrations, varying penetration by time of day and geography, and vehicle mix bias made direct comparisons of absolute trip counts potentially misleading. Addressing these issues became a core methodological focus of our work and a key discussion point during the poster session.
Key Findings: Not All Drivers Respond the Same
One key finding was that driver responses to the congestion pricing program were not uniform across vehicle classes. Passenger vehicles and light and medium-duty trucks/vans exhibited only modest shifts in their CRZ entry times. However, heavy trucks showed a pronounced behavioral response, substantially altering their travel patterns by shifting CRZ entry to late-night hours on weekdays and early mornings on weekends to take advantage of discounted toll periods. Additionally, our longitudinal analysis of users who were active in the CRZ in 2024 revealed a measurable behavioral shift, with CRZ-related trips reduced by approximately six percentage points following implementation.
From Research to Policy-Relevant Insights
These findings have important implications for transportation policy and operations. One potential application of our findings relates to transportation safety and operations. Our analysis indicates that heavy-duty trucks adjusted their travel patterns toward late-night and early-morning periods in response to discounted tolls. While this shift may help alleviate daytime congestion, it also highlights the importance of monitoring potential secondary effects, such as changes in nighttime traffic conditions, noise impacts, curb usage, and safety outcomes.
The findings also suggest an opportunity for agencies to periodically review and fine-tune toll structures by vehicle class and time of day to better align pricing objectives with observed travel behavior. These insights are relevant to policymakers, transportation agencies, and enforcement and safety stakeholders as they continue to evaluate and refine congestion pricing policies and supporting operational strategies.
Looking Ahead
The feedback we received during the presentation emphasized the importance of incorporating multi-source data to cross-validate and strengthen our INRIX-based findings. For our next steps, we plan to integrate additional datasets to corroborate our initial results. Furthermore, we aim to conduct long-term longitudinal monitoring to determine whether the behavioral shifts we observed are temporary reactions or permanent adaptations, providing a more complete picture of mobility trends following the implementation of congestion pricing in New York City.
Presenting at TRB and participating in the 2025 INRIX x MetroLab Challenge reaffirmed the impact that student-led, data-driven research can have on real-world policy discussions. It was a powerful reminder that transportation research doesn’t end in the classroom; it can directly shape how cities plan, price, and manage mobility for years to come.
Register now for the next Talk with the Experts Series: MetroLab Challenge Winners.
Learn more and apply here for the 2026 INRIX x MetroLab Challenge.