On January 5, 2025, New York’s MTA launched the Congestion Relief Zone tolling program, charging drivers a fee to enter the notoriously congested streets below 60th St. in Manhattan, excluding key highways and connector roads. The new toll, which includes peak and off-peak pricing, aims to reduce area congestion, air pollution, and safety risk, while raising revenue for the MTA. The tolling effort has implications not only for congestion in the immediate tolled zone but many surrounding areas, as well. (Federal administrators recently said they were rescinding approval of the tolling program, but as of this writing the tolls remain in effect.)

The MTA released initial data from week one of congestion pricing showing improved speeds on many of the bridges and tunnels entering the zone as well as on key bus routes.¹ Overall, most of the routes studied by the MTA have seen travel times improve.

StreetLight is now using its Traffic Monitor product, which helps planners and engineers monitor recent speed and congestion changes, to deepen the picture on congestion tolling with more data since the fee went into effect.

For a bird eye’s view of how traffic looked on a single day three weeks into the launch of congestion pricing, StreetLight used Traffic Monitor to create the gif below, showing the change in atypical speeds over the course of the day on January 28^th, as compared to similar days in January 2024. Green, thicker lines show improved speeds while red segments indicate decreased (i.e slower) speeds.

Of course, no single day provides a perfect measurement of traffic, as any day can be affected by crashes, weather, tourist activity, construction, and other disruptions.

To further contribute to the public’s understanding, StreetLight analyzed change in travel times over a three-week study period in January on ten distinct routes in the NYC metro area. You can see the map of the routes studied below.

StreetLight studied north-south routes, crosstown routes, and routes traversing areas outside the toll zone, in places where some have raised concerns about increased congestion from rerouting vehicles. StreetLight also included trips ending at major hospitals, as improving emergency vehicle travel times has been a stated goal of the program.

StreetLight’s analysis finds that most routes studied did see travel times improve. Six of the ten routes saw travel times decrease during both peak and off-peak tolling hours, including routes through New Jersey and Queens where there has been some resistance to congestion tolling.

Both Manhattan-based hospital routes – from Times Square to NYU Langone and the West Village to Memorial Sloan Kettering – saw peak hour travel times decline by 10% and 6%, respectively, a positive indicator for emergency travel within the zone.

For the routes where travel times worsened, the effect was small. Even during peak hours, the increase in travel times was less than a minute on all negatively impacted routes. This may be expected regardless of policy change as vehicle miles traveled have been steadily rising since 2021.²

Routes from New Jersey to Columbus Circle saw an interesting trend. Travel over the George Washington Bridge from Ridgefield Park, NJ to the northern edge of the congestion tolling zone slowed down by a slight 30 seconds during peak hours, as compared to a year earlier. However, travel via the Lincoln Tunnel from East Rutherford, NJ to Columbus Circle improved significantly, by over 3 minutes during peak hours.

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Analyzing Impact by Time of Day for Targeted Interventions

StreetLight allows planners and engineers to analyze travel at highly granular geographic and spatial scale. For example, if city planners are particularly focused on improving bottlenecks during the weekday AM or PM peak, that analysis is simple and straightforward. The impact of the MTA’s congestion charging will change over time as residents and visitors adjust, and as other trends impacting NYC arise. Many analyses will and should be done! StreetLight’s goal is to enable planners to understand and adapt to the complexities of managing congestion.

In the chart below, StreetLight compares the change in travel time on the Times Square to NYU Langone route by weekday only, looking at weekday all day vs. weekday peak AM and weekday peak PM. Peak AM travel times see the biggest improvement as compared to peak PM and all weekday.

Methodology

The analysis compares travel on select routes between January 5-25, 2025 and the same time of day and day of week for the month of January 2024. Travel times are based on sample count speed data.

Routes selected are not comprehensive of traffic in any one area. They represent travel between major destinations and aim to contribute to the picture of congestion pricing’s impact.

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1. Metropolitan Transportation Authority (MTA). Congestion Relief Zone Tolling: Week One Update. January 13, 2025. https://www.mta.info/document/162396

2. U.S. Federal Highway Administration, Moving 12-Month Total Vehicle Miles Traveled [M12MTVUSM227NFWA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/M12MTVUSM227NFWA, March 10, 2025.

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When Taylor Swift announced her first live tour since 2018, the rush on tickets by fans made national headlines (and earned a congressional hearing).

For transportation and transit agencies, and stadium operators, a very different challenge emerged: Managing traffic from the legions of fans who would descend on the stadiums for the Eras Tour.

Event operations pose a special challenge as they put a dramatic tax on roadway operations over a narrow time block, which local transportation infrastructure is not built to support during a typical day. As a result, stadium operations groups often work in close coordination with local transportation agencies to manage traffic, as well as ingress and egress from the stadium.

So when it comes to the Eras tour, how have the stadiums and agencies fared at managing fan traffic and keeping the roadways flowing? StreetLight ran the numbers to find out. Then, we look at how transportation and operations professionals can use analytics for more effective events traffic management.

Key Findings:

• Vehicle Hours of Delay (VHD) on roadways adjacent to the concert venues at least doubled during most Eras Tour concerts. On average, vehicle delays were 277% higher across all stadiums compared to delay hours at comparable times on non-concert dates. 
• Only four out of 23 venues saw traffic delays increase by less than 100%: MetLife Stadium in East Rutherford, NJ ; Mercedez-Benz Stadium in Atlanta, GA; Empower Field at Mile High in Denver, CO; and Acrisure Stadium in Pittsburgh, PA. 
• Traffic around MetLife Stadium, which invested heavily in transit access, actually decreased compared to usual delays. This is the only venue where traffic decreased. 
• The worst venue for increased traffic delays (based on % change from typical conditions) was Gillette Stadium in Foxborough, MA. This is a location where typical VHD is relatively low compared to many of the other venues studied. 

Eras Tour Traffic Winners & Losers

To understand the traffic impacts from the U.S. Eras Tour concerts, StreetLight analyzed Vehicle Hours of Delay (VHD) on all non-local roadway segments within a one-mile radius of each stadium during the peak arrival hour of 5-6 p.m. on each concert date. VHD measures the difference in vehicle travel time on a segment during congested versus free-flowing conditions, multiplied by the number of vehicles traveling on that roadway.  

This same process was repeated for the same days of week within that month (concert dates and holidays excluded) to determine a baseline VHD for a typical travel day. You can read more about StreetLight’s data here. 

Overall, across all 23 stadiums and 62 concerts, average delay hours were 277% higher than typical. In fact, all but four stadiums saw delay hours at least double on average over the course of the concerts. 

Two major success stories emerged, however: Atlanta’s Mercedes-Benz Stadium and New Jersey’s MetLife Stadium saw average delays well under 100%. 

Atlanta only saw a 32% increase in traffic delays. But NJ’s MetLife Stadium was the real standout. 

VHD actually decreased during the concerts, by 27% on average over the course of the three nights. Notably, both Atlanta and New Jersey’s concert venues were given high marks for their emphasis on public transit options to the concert. Atlanta’s Metropolitan Rapid Transit Authority System (MARTA) reported seeing three times the usual ridership during the concert days at stations near the stadium, according to CBSNews. NJTransit, which ran extra service around the stadium, carried 80,000 riders via train and bus to the concert, according to NJ.com. 

Of note, on a normal day, both MetLife Stadium and Mercedez-Benz Stadium see higher baseline congestion than most of the other stadiums studied here (with the sole exception of Vegas’ Allegiant Stadium). 

Philadelphia also placed a big emphasis on public transit. This may have paid off for the stadium on two of the concert nights. The Friday and Sunday shows in May 2023 at Philadelphia’s Lincoln Financial Field saw below average increases in delays compared to the other stadiums, with VHD 200% and 186% higher than typical for streets around the stadium, respectively. 

However, on Saturday night Philadelphia’s Lincoln Financial Field encountered huge snarls, with a 599% increase in hours of delay. This dragged down the stadium’s average across the three nights. It’s also a signal of how tenuous traffic management at an event like this can be, and how easy it is for delays to compound. 

But by far the worst increase in traffic delays occurred at Gillette Stadium in Foxborough, MA, near Boston. It saw delays 1,270% higher than typical on average over three nights in May 2023. Typical VHD near the stadium is low compared to many of the other venues in this study, perhaps because Foxborough, MA is a small town of just over 18k residents as of 2022, though its stadium regularly hosts sold out football games as the home of the New England Patriots, and is the largest stadium in the Greater Boston metro area. 

Next highest for percent increase in traffic delays, at 737% higher than typical, was Kansas City, MO’s Geha Field at Arrowhead Stadium. Like Gillette Stadium, this venue also sees relatively low typical VHD. 

Like Philadelphia’s Lincoln Financial Field, several other venues also saw dramatic differences in excess VHD depending on the concert date, including AT&T Stadium in Arlington, TX, Gillette Stadium in Foxborough, MA, and Geha Field at Arrowhead Stadium in Kansas City, MO. 

Among these venues, Saturdays and Sundays tended to see the worst increase in delays, with Fridays relatively lower. This could be influenced by commuter traffic on Friday evenings peaking between 5 and 6 p.m., driving up typical VHD on Friday evenings, resulting in lower increases comparatively. 

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How Transportation, Events, & Operations Professionals Can Manage Event Traffic Better

Events like the hotly anticipated concerts of Swift’s Eras Tour test the limits of everyday traffic operations, and often demand temporary strategies that reduce congestion, encourage shared transportation modes, and keep concert-goers safe.

But anticipating and mitigating traffic issues from special events is far from simple. To minimize delays, promote smooth traffic flow, and ensure safety, planners and operators need to know which routes attendees will travel, the modes they will use on the way, the intersections where they’ll be turning, and what alternate routes people may take as primary routes become congested.

Complicating these challenges is the time and financial cost of gathering the right data needed to understand all these factors. While certain major arterials may benefit from permanent traffic counters, many roadways lack these counters, such as residential or other local roads that may experience cut-through traffic when larger roadways become gridlocked.

This makes it impossible to get historical data with the granularity needed to understand past events or even average seasonal roadway conditions. Meanwhile, collecting data on complex roundabouts, intersections, or weaving segments can also be difficult, even if manual counts or surveys are deployed in advance of the event.

Big Data and Special Events Traffic Planning

A big data approach to special events planning can help fill crucial data gaps to anticipate their traffic impacts. Whether it’s used to inform broader travel demand models or applied for analysis of traffic operations during specific events, access to on-demand transportation analytics expedites special events planning without needing to put staff in harm’s way for manual counts and surveys that only capture a snapshot of traffic during a short period of time.

This expedited process allows planners and operators to proactively evaluate alternative traffic management strategies and communicate their decisions with the public in advance of special events.

Moreover, analyzing Origin-Destination of traffic, and routing to and from event venues can be particularly difficult when using traditional data collection methods, but it can also be one of the best starting points to understanding where and why congestion hotspots occur while also revealing underutilized road segments that could be used to free up traffic.

Big data makes analyzing top routes quick and simple so that traffic operations managers or planners have the best tools to ensure traffic flows smoothly.

When analyzing historical traffic data for special events planning, the following metrics can be helpful:

• Origin-Destination (O-D) and Top Routes – to anticipate where attendees are coming from, which roadways can expect the largest increase in travelers, and which less-used segments could be candidates for traffic rerouting.
• Turning Movements – to understand where and when people turn into and near the event venue during typical conditions and special events.
• Traffic Volumes – to understand where roadways may reach capacity and identify potential detour routes.
• VHD – to anticipate the impact and severity of traffic congestion during special events compared to average conditions.
• Speed – to evaluate safety conditions and crash risk near the venue, especially for vulnerable road users like pedestrians and cyclists.
• Travel Time – to understand how special events impact not just attendees but other road users and communicate expected delays to the public.
• Bike and Pedestrian activity – to identify common walking and cycling routes to and from the venue.
• Transit ridership – to understand available capacity for shared transportation modes that can help ease congestion.

Planners and traffic engineers can use these metrics to anticipate how traffic conditions will change during special events and prioritize traffic management strategies that will keep traffic flowing and protect the safety of all road users.

For example, examining turning movements at key intersections leading to the event venue could inform temporary signal retiming on the day(s) of the event to offer more opportunities for attendees to make their turns toward the venue. Likewise, identifying increased traffic volumes on residential or other local streets not suited for high-volume traffic could signal the need for signage directing event attendees to preferred alternate routes toward the venue.

Traffic operations managers can now also leverage real-time or near real-time data to monitor traffic disruptions as they develop and compare current speed and volume conditions to historical data to diagnose slow-downs or safety concerns and how to deploy the best solution quickly. StreetLight’s Traffic Monitor product can equip agencies and firms with real-time insights for any road, even newly constructed roads and other roads without physical counters. The gif below shows an example of atypical volumes around Las Vegas’ Allegiant Stadium during the 2024 Super Bowl.

To learn how you can leverage big data for special event and other traffic operations management, check out our Traffic Engineering and Operations Solutions.

Notice Something Different?

If you read StreetLight’s original analysis, covering the first nine venues of the Eras Tour in March–May of 2023, you may have noticed some differences in the results from the original analysis. 

To learn more about the methodological changes driving those differences and why the new data reflected in the above analysis improves upon the reliability of congestion insights, check out our new blog on Data and Methodology updates for February 2025. There you’ll find an in-depth explanation of how StreetLight’s new Network Performance analysis type compares to the Segment Analysis data we used for the original nine-venue analysis — and where stadium rankings differed slightly between the two methodologies. You’ll also find information on other recent reliability improvements to metrics like vehicle volumes and VMT. 

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Last weekend’s Super Bowl was the most watched television event in history. At Allegiant Stadium in Las Vegas, it was also one of the biggest in-person events of the year for the city. The stadium itself has an extended capacity to accommodate over 70,000 game-goers, but that doesn’t account for the tailgaters and partygoers who attended events throughout the city before, during, and after the game.

For event operators and transportation agencies that also means the Super Bowl was one of the biggest traffic bottlenecks of the year. (And that’s without factoring in Taylor Swift’s travel from private jet to stadium arena.)

To understand how traffic trends played out and compare the impact against other recent major events at Allegiant, StreetLight used its Traffic Monitor product, equipped with real-time and historical speed and traffic activity data. Understanding these traffic patterns — which roadways see the most congestion and when — can help event operators study and improve traffic plans for events and construction projects.

In the gif below, you can see a time lapse of Super Bowl traffic around Allegiant Stadium during the 12 hours around the game.

You can see how roadways build up atypical vehicle volumes (shown in gradient from yellow to red) throughout the day, ahead of the game start. But then, the gradient becomes light blue during the game itself, indicating lower than normal vehicle volumes. This is because vehicle volumes on roadways surrounding the stadium actually fell below normal during the game, as people stayed put both at the stadium or at their Super Bowl parties to watch the action. Volumes rise again, well above the pre-game volumes, after the game ends.

This is visible in starker relief in the screenshots below. in the first image, we see atypical volumes at the peak egress vs. the second image, where the roads are clearer than usual during the game.

Of course, events don’t take place in a vacuum and there may be unforeseen circumstances that further impact congestion. Las Vegas’ Super Bowl traffic offers an example of this as well.

Nearly simultaneous with the end of the Super Bowl and peak egress, a pole fell on the Las Vegas strip within 3 miles of Allegiant Stadium. StreetLight captured the impact of the incident on speeds on nearby roadways in the gif below.

The pole incident further contributed to the Super Bowl traffic impact, as congestion moved away from the Stadium and towards post-game events throughout the city.

This is another important consideration for traffic planners and engineers: what will the impact look like should some an additional traffic incident occur, and where are the potential routes and detours that can help disgorge some of those impacts. This is why it is critical to pair near real-time data with historical data to dynamically adjust for typical vs. atypical circumstances.

Event Traffic Trends at Allegiant Stadium

Las Vegas is a town that regularly hosts major marquee national events. But traffic around the stadium still snarls from the impact of attendees. In fact, when StreetLight analyzed Taylor Swift’s Eras Tour, it found that Allegiant Stadium saw the greatest vehicle hours of delay of any of the stadiums studied.

To get a high-level view of how congestion and traffic typically operates during events at Allegiant Stadium, StreetLight first measured Vehicle Hours of Delay within one mile of the stadium during peak arrival and peak departure hours at some recent events prior to the Super Bowl.

It’s clear that the timing of the events has a major impact on delays. Delays are much higher in the hour before the event when the event occurs on weekdays, likely because on these days there is higher typical congestion. Otherwise, egress is typically when there is the most concentrated congestion.

In the graphs below, StreetLight further analyzed major roads within a 3.5-mile radius of Allegiant at each of these events to understand the trajectory of roadway congestion during the 12 hours surrounding the events. StreetLight also used near real-time data to see these trends during the Super Bowl itself. The analysis measures the percentage of roadways with average speeds below 75% of typical free-flow speeds mapped over the 12 hours surrounding the 9 events and normalized for event start times.

Again, it’s evident how weekday events create much more congestion leading up to the event. In particular, Taylor Swift’s Friday concert dwarfs the other events for peak pre-event congestion, including the Super Bowl. Of course, that is in part driven by event excitement and fans arriving early to buy merchandise, but it is also likely a function of the Friday event time. The single NFL game studied on a weekday, the Monday Oct 9 game, sees the second highest congestion ahead of the event start, ahead of even the Super Bowl.

In fact, pre-event traffic to the Super Bowl follows very similar patterns to the other weekend games, although the period of sustained congestion is slightly longer and earlier than the other events.

The Super Bowl is also not a complete outlier for egress congestion, though traffic did push slightly later, perhaps due to the game going into overtime. Congestion is also sustained for a somewhat longer period during egress compared to all the other events. This could be a reflection of Super Bowl-specific attendance trends, the impact of the downed pole on the strip, and even increased traffic throughout the city as people outside the stadium also got back in their cars following the games.

To disentangle normal traffic patterns from event-induced traffic, StreetLight’s tool allows users to compare empirical speeds to free-flow speeds and typical speeds for a given corridor.

In the two charts below, StreetLight shows the differences in these measures across three of the events studied: Taylor Swift’s Friday concert, the Super Bowl, and another Sunday NFL game. The scale in the free-flow chart is higher because the percentage of congested roadways is higher when empirical speed is compared to free-flow speeds.

The spike in traffic from Taylor Swift’s Friday concert is more compressed when compared against normal speeds because this measure better accounts for existing weekday traffic. During egress, Swift’s concert and the Super Bowl look similar across both measures.

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Big Data for Special Events and Construction Traffic Operations

A big data approach to special events planning can help fill crucial data gaps to anticipate the traffic impact of special events and deploy rapid-response congestion mitigation measures during these events to ease clogged traffic.

Access to on-demand transportation analytics can be used to inform broader travel demand models, analyze past events to inform future event operations, and monitor ongoing events as they unfold. These kinds of insights are critical for dynamically adjusting plans and identifying safety concerns. And because analytics are accessed online, this can expedite special events planning without putting staff in harm’s way for manual counts and surveys that only capture a snapshot of traffic during a short period of time.

This expedited process allows planners and operators to proactively evaluate alternative traffic management strategies and communicate their decisions with the public in advance of special events.

Meanwhile, near real-time traffic data can help operations managers monitor traffic during an event and react quickly to congestion or safety concerns as they develop. Using near real-time data to create a high-level view of congestion throughout the roadway network over time (i.e. viewing a time lapse of traffic conditions like vehicle speeds) can help spotlight where capacity is strained and where there may be potential to reroute traffic to underutilized roadways.

Historical Traffic Data for Special Events Planning

Analyzing historical traffic data can help proactively plan special events traffic management. In particular, these metrics may be helpful:

• Traffic Volumes – to understand trends over time, identify when during the day traffic peaks, compare weekdays to weekends, and flag where road capacity may be insufficient and identify potential detours.
• Origin-Destination (O-D) and Routing – to understand where attendees tend to travel from, which roadways may become congested, and where traffic could be rerouted to less-used segments to ease traffic flow.
• Turning Movements – to pinpoint major intersections and road segments where people turn on their way into the event venue during typical conditions and special events.
• VHD – (Vehicle Hours of Delay) to understand how past events have impacted traffic congestion on roads near the venue, and how these conditions affect the larger roadway network.
• Travel Time – similar to VHD, travel time analyses can help planners understand how special events impact all road users (not just attendees) and inform public communications around expected delays.
• Vehicle Speeds – to evaluate safety conditions and crash risk near the venue, especially for vulnerable road users like pedestrians and cyclists.
• Bike and Pedestrian activity – to identify common historical walking and cycling routes to and from the venue.

These metrics allow planners to anticipate how traffic conditions will change during special events and prioritize traffic management strategies such as detours, signage, and signal timing that will keep traffic flowing and protect the safety of all road users.

For example, analyzing turning movements by time of day can reveal key intersections leading to the event venue that are well-timed for normal conditions, but stall traffic flow during major events. Planners may use these insights to temporarily retime signals on the day(s) of the event, or specifically during the hours that turning movements peak, to offer more opportunities for attendees to make their turns into and out of the venue. Similarly, planners can flag where event signage could be necessary to direct traffic away from residential or other local streets not suited for high-volume traffic.

Near Real-Time Traffic Data for Special Events and Construction Planning

Near real-time traffic data can be used to respond quickly to road conditions as they change, giving operations managers more insights into the specific tactics that can help mitigate congestion or safety concerns during the atypical traffic patterns that accompany major events like the Super Bowl or during significant construction projects.

For example, operations managers might notice major delays on a specific corridor leading into or out of an event venue. They might then analyze recent vehicle traffic activity on adjacent streets to see where rerouting cars could unjam traffic, or pinpoint the most congested intersections to deploy temporary traffic control personnel or retime smart traffic signals to improve traffic flow.

Analyzing near real-time vehicle speed and traffic flow metrics can also help operations managers pinpoint where pedestrians may face dangerous conditions, allowing them to deploy traffic calming measures quickly if needed.

Near real-time data can also be useful ahead of an event or major construction to understand the most recent traffic trends and inform communications with the public regarding expected delays or detours. This can be especially impactful if there have been recent design changes to nearby roads or the venue itself that may impact traffic flow patterns.

To learn more about leveraging big data for special event, construction, and other traffic operations management, check out our Traffic Engineering and Operations Solutions.

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