Road conditions can change rapidly. A fallen tree or flooded bridge might force cars to detour onto adjacent streets. Lane closures during road work can create bumper to bumper traffic. A crash may block lanes and require immediate response.

For agencies managing many miles of roadway and moving thousands (or even tens of thousands) of vehicles hourly, keeping traffic flowing smoothly and safely can be difficult enough during typical conditions. So, disruptions – planned, unplanned, or recurring – can quickly stall traffic or create unsafe conditions for everyone on the road. And the longer it takes for Traffic Operators, Engineers, and Planners to respond to disruptions, the worse conditions may get.

That’s why Traffic Operations teams are turning to transportation data to achieve smoother closures and detours, faster incident detection and emergency response, and proactive communication.

In the past, operators have had limited visibility into their road networks. While some major thoroughfares and intersections may have permanent sensors installed that can help operators spot unusual conditions, many roadways lack these sensors, forcing operators to send staff into the field for a first-hand look at conditions or wait on complaints from road users or reports from incident responders before they’re aware of an issue.

But today, access to transportation big data enables operators to monitor what’s happening on their entire road network in real time and investigate historical traffic patterns in minutes to get ahead of future disruptions, contextualize what’s happening now, or learn from past disruptions.

In this report, we’ll explore how you can leverage the latest advancements in transportation data for:

• Daily roadway operational performance and congestion mitigation
• Construction management and lane closure/detour planning
• Special events management
• Evacuation scenarios
• Effective incident response
• Clear communication with the public (e.g., on travel times, closures, detours)

1. Address Congestions and Speeding on Key Routes

Vehicle registrations are on the rise¹ and despite a brief lull during COVID, congestion is back with a vengeance across the U.S. This makes identifying and addressing bottlenecks a persistent challenge for operators. How do you mitigate slowdowns before cars become gridlocked and stop congestion from recurring?

Meanwhile, fatal crashes reached a 16-year high in 2023, with nearly a third of them involving speeding — and the situation hasn’t improved much since.² How can operations teams address speeding before the next crash and ensure improvements remain effective?

Analyzing real-time and historical traffic data is key to answering all these questions. Solutions like StreetLight’s Traffic Monitor product can help alert you to atypical volumes and speeds happening right now across your road network and compare current conditions to historical baselines to contextualize their severity.

Because congestion and speeding may have many causes, analyzing historical traffic patterns is key to diagnosing the ‘why’ behind persistent hazards and identifying effective solutions. Here are just a few examples:

• Are commuting patterns a main cause of congestion?
  • Analyze vehicle volumes, speeds, and travel times by time of day, day of week, and direction to see if there are consistent peaks and dips.
    
• Does congestion ebb and flow during the year?
  • Compare seasonal traffic trends to understand how tourism, recreation, academic calendars, or other events may impact traffic.
    
• Could other routes help alleviate slowdowns on your most congested corridors?
  • Investigate where traffic spills over during congestion to inform effective detours and communicate them to the public.
    
• Are drivers complying with detour routes?
  • Investigate atypical volumes to understand which alternate routes drivers are actually taking and how it’s impacting congestion.
    
• Do specific destinations drive the bulk of traffic?
  • Analyze common origins and destinations to determine where transit routes or multimodal infrastructure can help reduce the number of vehicles on the road.
    
• Where are the speeding hotspots in your road network?
  • Analyze average vehicle speeds to see where driving patterns don’t align with posted speed limits and evaluate potential solutions like speed feedback signs or temporary road diets.

Data in Action: Identifying recurring bottlenecks in Downtown LA

Los Angeles, California is notorious for traffic congestion due to multiple factors, including commuters crowding freeways during rush hours and major events at venues like SoFi Stadium or the Hollywood Bowl. This creates recurring bottlenecks throughout the city that can cause driver frustration, slow down emergency response, and delay goods from reaching their destination.

Using its Traffic Monitor product, StreetLight went back in time to investigate historical vehicle speeds and quickly zero in on the most severely congested corridors. Using Wednesday, July 23, 2025 as an example of typical weekday traffic, StreetLight then used the timeline feature to see how vehicle speeds change throughout the Downtown LA road network over the course of the day.

Actionable takeaways:

• Morning slowdowns are common on key routes, but evening congestion is more severe and begins as early as 3pm.
  
• By 5pm, congestion doesn’t just impact major corridors but also spills over to local roads throughout downtown.
  
• Northbound traffic is especially congested in the evening on corridors like the Santa Ana and Santa Monica Freeways as commuters return home to the suburbs.

🎞️ Watch the full analysis here.

2. Keep Traffic Flowing During Construction and Events

Road construction and special events are among the most predictable causes of traffic disruptions — and among the most costly and frustrating, too. But by learning from past projects and monitoring current conditions, you can minimize disruptions — and the complaints that come with them.

There are many ways to use historical traffic data to prepare for upcoming construction and events:

• Need to close one or more lanes?
  • Review historical vehicle volumes by time of day and day of week to identify optimal closure windows and understand how a partial vs. full closure may impact nearby roads.
    
• Closing an entire road?
  • Choose the right detours based on historical routing patterns and capacity on alternate roadways.
    
• Want to ensure safe work zones?
  • Analyze historical vehicle speeds and queuing patterns to meet CFR requirements and determine where safety measures like barriers or variable message signs could mitigate risks.
    
• Planning traffic management for an upcoming event?
  • Review traffic patterns on past event dates and times to see if adjusting signal timings near venues or deploying resources like signage or traffic controllers could help.
    
• Looking to streamline future event planning and operations?
  • Evaluate traffic management outcomes on previous event dates to identify effective strategies and create repeatable event traffic management playbooks.

Real-time data can also help you ensure safe, flowing traffic during construction and events, and highlight opportunities to quickly deploy congestion mitigation or safety interventions:

• Queues forming ahead of work zones?
  • Measure queue lengths to meet federal regulations for work zone performance³ and determine where queue warning signage or other end-of-queue crash prevention measures may be needed.
    
• Event egress causing gridlock?
  • Identify and communicate where the bottlenecks are to improve travel experiences and see where adjusting signal timings or deploying traffic controllers could help.
    
• Travel times increasing considerably during ongoing road work?
  • See how current travel times compare to recent fluctuations to determine whether you need to adjust road work windows, implement congestion mitigation measures, or notify the public.
    
• Road work having minimal impacts on traffic flow?
  • Review fluctuations over the course of the day and week to see if road work windows could be safely expanded to complete the project faster.

Data in Action: Improving football fan experiences at Northwest Stadium

Northwest Stadium, the 70k-seat home of the Washington Commanders, has a congestion problem. The 2024 NFL Voice of the Fan survey reported that game day experiences at the stadium were among the lowest rated in the league, with only 15% of attendees finding it easy to arrive and depart from the stadium.

To shed light on where, when, and why game day congestion occurs, StreetLight used its Traffic Monitor product to compare two game days where road conditions differed:

Traffic patterns shift during a blowout vs. close game

December 1, 2024 – Sure Win

As the game’s end neared, it was clear the Commanders would defeat the Titans. Some fans left the stadium early, resulting in fewer vehicles exiting at once and less congestion on I-95.

• DELAYS: Up to 30 minutes
• QUEUING: Up to 48% of the route queued

December 22, 2024 – Close Game

Commanders pull off a win against the Eagles on the final play of the game. Many fans stayed in their seats until these final exciting moments, resulting in a surge of exiting vehicles on I-95 and a huge peak in travel time.

• DELAYS: Up to 52 minutes
• QUEUING: Up to 76% of the route queued

These insights can help operators prepare for a variety of scenarios and evaluate potential improvements.

Additionally, operators can monitor real-time conditions on these key routes on game days to spot whether temporary interventions are needed and communicate current travel times and incidents with the public.

🎞️ See what else you can do with the Queuing feature in this video.

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Data in Action: Minimizing construction impacts in Des Moines, Iowa

To resolve operational issues at the I-35/80 interchange in Des Moines, Iowa DOT needed to add lanes, install a new interchange, and widen multiple ramps. But this project area sees the highest traffic volumes in the state alongside high incident rates, and overlapped with other construction projects happening during the same time frame.

To minimize disruptions, Iowa DOT used StreetLight’s Traffic Monitor during construction to answer questions like:

• When are vehicle volumes low enough to accommodate lane closures?
• Can the local street network handle additional traffic during closures?
• Are people avoiding this section of the interstate?
• What other routes are people taking? Are detours working?
• Which ramps are being used while ramp closures are in place?
• How do work zone crashes impact the transportation system?

Traffic Monitor’s real-time insights enabled Iowa operators to plan effective lane closures and detours and share up-to-date information on delays, volumes, and speeds with first responders, city officials, and businesses that are impacted by the project.

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3. Respond Faster to Unplanned Disruptions

To detect and address incidents like crashes, objects in the road, broken traffic lights, inclement weather, and more, agencies typically either need sensors installed wherever the incident occurs or staff in the field to report on conditions. But neither sensors nor staff can be present on all roadways at
all times due to high installation costs, dangers to staff, weather conditions, and other limitations. That
means incident detection and response is often subject to inevitable delays, further compounding congestion and safety.

But today, real-time transportation data can help fill these coverage gaps, enabling operators to detect incidents just moments after they occur and rapidly deploy the necessary resources to address them. Likewise, with information in their hands more quickly, officials can communicate clearly with
the public in a timely manner, updating drivers on travel time delays, temporary closures and detours, and more.

Plus, by comparing real-time conditions to historical baselines, operators can quickly contextualize the severity of an incident. But even with this wealth of data, keeping an eye on what’s happening across your entire road network at all times would be a colossal task. How do you quickly sift through current
conditions on your roads and zero in on issues that may need your attention?

Tools like the Real-Time Incident Feed in StreetLight’s Traffic Monitor product can help alert operators to atypical conditions, their severity, and potential causes. Traffic Monitor’s Real-Time Incident Feed displays up-to-date information on:

• Full and partial road closures
• Ongoing road works
• Crashes

This helps shed light on not only where atypical traffic patterns are occurring but why and how severe their impacts are so you can prioritize effective solutions where they’re needed.

Data in Action: Improving Future Evacuations with Data from Hurricane Ian

Extreme weather can be volatile, with forecasts shifting quickly. When Hurricane Ian changed course 24 hours before its expected landfall in September 2022, its unpredictable trajectory complicated traffic management efforts for Florida officials.

StreetLight investigated what happened on evacuation routes 48, 24, and 8 hours before the storm’s landfall to understand where travel demand surged and what operators can learn for future evacuation scenarios.

Our Traffic Monitor analysis revealed that:

• 48 hours before landfall, traffic conditions were relatively normal, with no peaks observed in vehicle volumes in either city.
• 24 hours before landfall, a surge in vehicle volumes hits key routes out of Fort Myers, especially Palm Beach Blvd, where volumes are 2-3x higher than usual. Around the same time, vehicle volumes are also 2-3x higher than normal on routes entering Fort Lauderdale.
• 8 hours before landfall, vehicle volumes drop off dramatically, indicating evacuation procedures had completely stopped by this time.

Before the next evacuation scenario, planners can use historical insights like these to understand:

• Did people comply with evacuation instructions? Why or why not?
• What routes did evacuees use? Were they the ones they were supposed to use?
• When did people start and stop evacuating?
• When did vehicle volumes peak, and how long were the traffic delays?
• What best practices can I take away from these outcomes to inform future scenario planning?

During an evacuation, operators can also use real-time data to monitor how evacuations are going and coordinate rapid response to keep people safe:

• When should the evacuation process begin to get everyone out safely?
• Are people complying with evacuation orders and routing instructions?
• Are there any crashes or other incidents stalling traffic on key routes?
• Where should resources be deployed to support more efficient evacuations?
• What do I need to communicate to the public during this critical time frame?

🎞️ Watch the full analysis here.

Data in Action: Understanding the ripple effects of a holiday crash in Colorado

On July 3rd, 2025, a fatal crash closed I-70 just as a surge of visitors was traveling to the Colorado Rocky Mountains for the Fourth of July weekend. As responders worked to address the situation and evacuate stuck vehicles from the roadway, the traffic impacts were being felt throughout the nearby road network and would linger long after the incident.

Real-time data can help operators limit the duration and severity of closures during similar incidents and understand their ripple effects across the road network to inform temporary detours and other traffic control measures.

StreetLight used its Traffic Monitor product to understand what happened before, during, and after the crash, which occurred around 1 p.m.:

• That morning, traffic volumes were higher than typical as holiday travelers hit the road.
• After the crash, traffic came to a standstill for miles behind the crash location.
• Ramps leading up to the crash were clogged as vehicles attempted to escape the traffic jam.
• To avoid the impacted section of I-70, travelers rerouted onto US Hwy 6 and US-40, clogging these highways as well.
• Even after lanes on I-70 were fully reopened, the build-up of previously stranded vehicles and drivers reentering the interstate combined to create major congestion issues lasting for 4 more hours.

These ripple effects would be difficult to spot without real-time data on the entire road network. While major roadways like I-70 may have sensors installed, smaller detour routes often do not, making it difficult to understand and address impacts on these roadways.

Understanding the full scope of an incident’s impact on the road network can help officials minimize future dangers and disruptions by:

• Identifying where additional resources may be needed
• Establishing the best detour routes
• Communicating proactively with the public

Labor Day weekend travel is an American tradition, capping off the traditional summer season. But how much does Labor Day travel actually impact driving patterns? StreetLight analyzed trip patterns in the top 50 U.S. metros to see how Labor Day trip volumes, lengths, and travel times compare to a typical Friday.

Understanding leisure ground travel patterns is critical for public sector agencies managing traffic during major peaks in activity, as well as for private sector businesses dependent on tourism activity. Think rest stops, fueling stations, toll operators, roadside motels, restaurants, and vacation hubs, among the many other businesses that serve road trippers.

To understand how the U.S.’s biggest metros compare when it comes to road trippers fleeing the city for one last hurrah, StreetLight used its industry-leading transportation analytics to analyze vehicle travel trends across the largest metropolitan areas.

StreetLight analyzed the 50 largest Metropolitan Statistical Areas (MSAs) by population to understand how travel activity compared on the Friday before Labor Day in 2024 versus a typical Friday during the fall, analyzing by difference in:

• Share of out-of-town trips 
• Total trips 
• Average trip length 
• Average travel time  

At the end of the analysis, you can see complete results alphabetized by metro.

Key Takeaways

• Labor Day Friday does not see as big an uptick as might be expected in the share of trips leaving cities vs. a typical Friday.  

• The largest increase occurs in Minneapolis, with the share of leaving trips increasing by 1.5 percentage points, followed by Raleigh and Richmond. 

• Even more surprising: In nearly every metro studied, fewer total trips take place on Labor Day Friday vs. a typical Friday. Only nine of the top 50 metros see total trips increase on Labor Day Friday as compared to a typical Friday. 

• The popular tourist metros of Tampa, Jacksonville, and Las Vegas see the biggest increase in total trips on Labor Day Friday. 

• Overall, Hartford sees the biggest share of trips heading out of town on a typical Friday, accounting for about 15% of trips. Raleigh and Salt Lake City see the next highest shares, at roughly 10% each.

Labor Day Friday vs Typical Friday Travel Trends

For anyone who’s tried to get to get out of town on the Friday before a holiday weekend, it may be a surprise to learn that the share of trips leaving the region actually does not increase substantially. In fact, the largest increase in share of trips that exit the city among the metros is Minneapolis with an increase of 1.5 percentage points, from about 4.5% of trips on a typical Friday to 6% on Labor Day Friday. That said, while a 1.5 percentage point difference might seem small, it still represents just over 100,000 trips. 

After Minneapolis, the next metros with the biggest bumps in share of trips leaving the city for the long weekend are Raleigh, NC: Richmond, VA; Grand Rapids, MI; and Philadelphia, PA. 

Percent Change in Share of Trips Leaving Metros, Labor Day Friday vs. Typical Friday

Even more surprising than the relatively small bump in share of travel out-of-town: There are fewer total trips in most metros on Labor Day Friday as compared to a typical Friday. This may reflect people not commuting to work and thus driving down trips in general. Only nine of the top 50 metros see total trips increase on Labor Day Friday as compared to a typical Friday. 

Tampa, Jacksonville, and Las Vegas top the rankings for increased trips overall on Labor Day Friday. Each of these cities are car-oriented tourist destinations that may see locals and out-of-towners alike traveling around the metro. 

Percent Change in Total Trips on Labor Day Friday vs. Typical Friday

Hartford is the metro where the biggest slice of trips head out of town on a typical Friday, even as the city does not see a notable bump in share of trips leaving the city ahead of Labor Day. Metros with a large portion of typical Friday “leavers” may have a high proportion of long-distance commuters or a significant outdoor culture taking them farther afield on a typical weekend.

Share of Trips Leaving Metros on a Typical Friday

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For change in average trip length on Labor Day Friday, Raleigh and Minneapolis rank first and second, with Richmond coming in third. This ranking closely tracks the ranking for increase in share of trips out-out-town. Charlotte and Birmingham are the only cities that appear in the top five for increased avg. trip travel length but not in the list for increased share of trips out of the metro.

Percent Change in Average Trip Length, Labor Day Friday vs. Typical Friday

And Atlanta enters the top five for overall increased average travel time on Labor Day Friday. The other metros in the list align closely with the top five for increased trip length. Minneapolis is the only one of these metros where trip length increases by a greater percentage than travel time.

Percent Change in Average Travel Time, Labor Day Friday vs. Typical Friday

By examining empirical data on vehicle activity, we can see that the typical stories we hear in the media about Labor Day “traffic armageddon” are actually far more nuanced. Total trips on Labor Day Friday, in fact, go down in most cities. And trips leaving the metro region increase by far less than we might expect.

For this analysis, we used StreetLight’s historical trip data to investigate total trip volumes, trip lengths, and travel times across the U.S. To dive deeper on your area’s travel trends and power more informed planning, operations, or business decisions, StreetLight offers unmatched spatial and temporal precision across a wide range of metrics, including origin-destinations, top routes, trip purpose, and more.

Check back in the fall when we’ll use our Vehicle Tours data to understand the most popular road trip destinations among the top metros.

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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.

___

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. 

Data-driven ways to avoid travel delays, transit "crush loads" and more during events

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