Commutes Across America – Where are the Longest Trips to Work? Part 2

Commutes Across America – Where are the Longest Trips to Work? Part 2

After a long day at work, you probably want to get home as soon as possible. But, on most days, that’s easier said than done.

Today, commutes across America are longer than ever – and they’re increasing. The average American commutes 52 minutes to work each day, for a total of 4 hours and 20 minutes per week. Think of all the productive ways you could be spending that time, rather than sitting in your car or crammed in a crowded subway.

In our last blog about commutes, we explored where some of the longest commutes to work are in America. Now, let’s learn more about why areas have long commutes and how Big Data can be used by transportation planners to help mitigate this problem

Why Some Commutes Across America Are So Long

So, why are commutes to work long? There are a number of factors. First, there are large population concentrations in the suburbs. As the cost of living in city centers increases, people relocate to the suburbs, which means they often have to commute into the city for the best jobs.

Next, due to urban and suburban development, construction is a regular feature of many people’s daily commute. Doesn’t it seem like there’s always something under construction in your area? Because commutes are increasing, roads need to be reconfigured to accommodate more people. And, there’s the regular construction to upkeep roads, too.

Solo commuting plays a role, as well. Most commuters today don’t carpool, choosing the freedom that comes with driving their own car to or from work. Over 90% of trips to work happen in cars, which equates to more cars on the road and slower commutes.

How Data is Collected

Each minute, millions of mobile devices collect data points that can hold valuable insights for transportation companies or urban planners. But, this raw data collected from phones, tablets, or GPS devices can be hard to translate into actionable transportation plans. So, you need a partner like StreetLight Data to help. StreetLight Data is a technology company that transforms Big Data from mobile devices into actionable analytics for transportation infrastructure and policy planning.

Using a solution like StreetLight Data’s StreetLight InSight^® platform helps because it collects and condenses all of the data resources alongside processing software in one easy-to-use tool. You save time by not going out and finding the best Big Data resources yourself from different vendors, or by trying to organize and analyze data yourself outside of a proven framework.

Once the raw data is collected, it’s processed and presented as a number of different, customizable and insightful analytics to users. These analytics includes:

• Origin-Destination Matrices
• Traffic Diagnostics
• Corridor Studies
• Trip Purpose
• Demographics
• Average Travel Times and Travel Time Distributions
• 2016 AADT (Average Annual Daily Traffic)
• Commercial Truck Studies

How Data Helps Shorten Commutes

While the data collection process may seem intricate, the results it produces can be applied to a number of different transportation modeling, forecasting, and planning activities. And these activities can help you design better project and policy solutions that reduce – or even eliminate – long commutes for citizens. These include:

• Creating and calibrating travel demand models
• Evaluating before-and-after studies to determine project impact
• Prioritizing tasks and creating cost/benefit analyses for projects
• Busting congestion
• Routing detours
• Designing, expanding, and analyzing public transit systems
• Changing toll systems and signals
• Employer incentive programs
• Acting as supporting materials for public meetings and communications

Each of these transportation projects could help improve commutes in your area and shorten the drive for millions of Americans. With the right data insights, you can pinpoint exactly where problem areas are, the factors behind those problems, and the solutions that can help address these issues.

The Road to Becoming a Transportation Rockstar

Transportation data can be used by a number of transportation professionals, both in the public and private sectors. Here’s how data ensure you and your team successfully shortens traveling commutes.

How  Transportation Planning Consultants Can Improve Projects Using Big Data

The success of private transportation firms is dependent on completing projects effectively and efficiently. With transportation analytics, you have the insight needed to properly plan and execute your projects. You’ll also be able to find creative solutions that could act as a competitive advantage over other firms bidding for the same projects. Plus, data can provide insights to show the return on an investment in your projects, like how building toll roads can shorten commutes.

How Public Sector Planners Can Improve Commutes for the Community

No community is like your community. Big Data helps you find the precise solutions you need to shorten traveling commutes, like improving your public transit system and first-mile/last-mile solutions, implementing new carpooling programs, and designing active transportation infrastructure.

One concern you may have as an urban planner is that the steps you take to improve commutes might not solve the problem. In the past, without data in your corner, this was a definite possibility. Today, when you use data, however, you can mitigate that risk by being sure of the factors that impact commutes. Even better, you can easily measure project performance as you implement different solutions and adjust your strategy to optimize results.

What the Government Can Gain by Using Big Data for Commutes Across America

For the federal government, data is essential for comparing commutes nationwide. This helps the government pinpoint areas that might need more federal funding for road projects or to improve public transit systems.

Data is also beneficial when it comes to nationwide initiatives. For example, the U.S. Green Building Council was able to use Big Data for transportation to better characterize commute distances.

If you’re ready to cut down on commutes in your community, it’s time to turn to Big Data. Get the analytics you need to understand the factors behind long commutes in your area and develop effective strategies to address these challenges. With StreetLight Data on your side, you’re sure to translate Big Data analytics into performance-driven results.

Commutes Across America – Where are the Longest Trips to Work? Part 1

Commutes Across America – Where are the Longest Trips to Work? Part 1

Are you tired of the long drive to and from work? This is probably the most tiresome, frustrating part of your day. And, you’re not alone. Everyone on the roadway probably feels the same!

To better understand commutes across America, StreetLight Data has compiled information on where commutes are the longest. Explore this article to find out why it’s important to understand commute travel patterns and to discover the top five states and cities with the longest commutes.

4 Reasons Why Understanding Commutes Matters

1. Commutes Impact Happiness and Health

As you sit in your car during your commute to or from work, you probably feel frustrated and stressed. Aside from being an inconvenience, a long commute could actually impact your health and happiness, too.

First, it’s important to note that the average American professional spends about 52 minutes commuting each day, according to the U.S. Census. That’s a lot of time that could be spent in better, more productive ways. You could be with your family, or even getting more work done. Instead, you’re commuting.

Next, let’s look at the impact of commutes on your health. According to a study in the American Journal of Preventative Medicine, commutes longer than ten miles have negative impacts on cardiovascular health. “The study found that people who drove longer distances to work reported less frequent participation in moderate to vigorous physical activity and decreased CRF (cardiorespiratory fitness), and had greater BMI (body mass index), waist circumference, and blood pressure.”

Finally, your happiness is at stake, too. In another study from National Geographic fellow Dan Buettner, it was reported that “if you can cut an hour-long commute each way out of your life, it’s the [happiness] equivalent of making up an extra $40,000 a year if you’re at the $50- to $60,000 level.” While a longer commute for a certain job may add more money to your bank account, it also reduces happiness from your life.

2. Commutes Contribute to Economic Inequality

Why do people drive so far to work? Many people commute just to have a job or to have a job that pays well. Others commute from suburban areas with lower costs of living to urban areas with more business and greater job opportunities.

So, how does this perpetuate economic inequality? Commutes cost money and time. If workers are expected to travel 20+ miles every day to get to work, that might not be a sustainable lifestyle. By looking at commute data, governments can step in and take action to close the accessibility gap.

3. Commutes Have an Environmental Impact

The longer you’re in your car during a commute, the more carbon dioxide your vehicle is emitting into the air. In fact, motor vehicles emit 20 pounds of carbon dioxide per gallon of gas burned. That translates into a national average of 5.5 tons of carbon dioxide emission a year for every motorist. Those emissions have a huge impact on the environment.

While there are options to cut down on the environmental impacts of commuting, like carpooling, telecommuting, or public transit, most people – 77% of motorists – still drive alone to work. And, work-related driving is responsible for nearly 30% of miles traveled in a vehicle. To cut down on those numbers, transportation planners need a better understanding of what commutes across America look like.

4. Commutes Should be Put in Context

Finally, it’s important to understand your community’s commute in context. How does your area stack up against other states and cities? Answering this question helps two groups. First, it’s crucial information for urban planners. When urban planners understand their community’s commute in context, they’re better able to identify what changes need to be made, and where they’re doing things right. Looking at similarly sized cities can reveal alternative transportation methods that could work in your own city.

Understanding commutes to work in context can also help workers make informed decisions for the future. While everyone feels like their commute is unbearable, the number might show that it could be worse. If your commute is better than those around you, you might stay at your job longer. If your commute is longer than your average commute, you might begin searching for a new job closer to home.

Commutes Compared: States and Cities

Now that you have a better understanding of why we think researching data on traveling commutes is important, let’s look at the states and cities whose drivers commute the longest distances.

Top 5 States with the Longest Commutes

Top 5 Cities (CBSAs) with the Longest Commutes

To understand city-wide travel patterns, we looked at CBSAs, or core-based statistical areas, which are a census designation for “one or more counties anchored by an urban center of at least 10,000 people,” plus neighboring counties with socioeconomic links to the urban center due to commuting.  Keep in mind that statistics related to low population areas can be heavily impacted by a small number of commuters who drive long distances.

Why this Data Matters and How to Put Big Data to Work for Your Transportation Projects

Commuter data is key to finding actionable solutions for the problem. With these insights, transportation and urban planners are equipped to make insightful decisions regarding transportation planning for the future. These data points also reveal areas that may need extra attention to make commutes to and from work shorter.

Consider incorporating Big Data analytics into your transportation and urban planning process. When you do, you’ll have better insights into the commuting habits of your community, and you can find solutions to alleviate the burden of their commutes. For more information on this topic, check out the blog next week to read part two of this series on commutes across America.

3 Challenges With Transportation Data Collection and How to Solve Them

3 Challenges With Transportation Data Collection and How to Solve Them

At the heart of every transportation project lies the need for mobility data. But actually getting accurate, comprehensive data in a cost-effective, appropriate, and timely manner is not always easy. Many transportation planners must rely on costly, outdated data or use time-consuming, assumption-based models to estimate behavior. Although surveys and sensors can certainly reveal important insights, planners who rely solely on conventional data collection tools often struggle to answer important travel behavior questions empirically, accurately, and comprehensively. But transportation planners can take control and get better results by taking advantage of new, more cost-effective, and more efficient data collection and analysis tools. In this blog post, we’ll discuss three key transportation data challenges, and how to overcome them by collecting data that is current and precise, and that describes real-world travel patterns.

The Status Quo

Due to both limited data collection budgets and inadequate data collection tools, projects can fall short of meeting localities’ evolving needs because they do not fully account for current travel patterns. Conventional methods and the data they produce (i.e.: inaccurate models calibrated with old data, incomplete trip information from tools like Bluetooth sensors, and license plate photographs matched to DMV records), do not give transportation planners all of the information they need to understand, evaluate, and forecast communities’ needs. Instead, they must extrapolate and estimate from the limited data sets available. And in some cases, political priorities can overshadow the priorities that the real-world data points to.

Challenge #1: Limited Budgets for Data Collection

Working with limited budgets means that transportation planners are often competing with other agency priorities for their projects. Creating competitive proposals without the proper data foundation makes it difficult for planners to capture the funding they need to develop proactive, long-term transportation projects.

When they rely on data that policymakers and civilians do not trust or do not fully understand, planners often fail to build buy-in from political actors, and they struggle to attract champions that will push their legislative priorities forward. As a result, many transportation agencies are forced into a pattern of short-term, and often expensive, fixes, or they find themselves pursuing “pet projects” instead of the ones that will make a long-term impact. For example, they repeatedly expand highways instead of finding permanent ways to reduce travel demand. Breaking this cycle requires a solid data collection and analytics tool.

Moving to an approach that prioritizes real-world data allows transportation planners to be more strategic in their funding requests, and to build a stronger base of support from policymakers. Real-world data allows planners to more objectively evaluate the long-term value and return-on-investment for each potential project, and present persuasive cost-benefit analyses to policymakers. This makes it easier to make the case for more funding because they can prove how each project they propose will add value, and rank them for stakeholders in order of impact.

This data-driven approach also makes it easier to access more varied sources of funding from private and public local, state and national sources. With the funding of the FAST (Fixing America’s Surface Transportation) Act  in December 2015, Congress provided $305 billion for transportation issues from fiscal years 2016 through 2020. Funds have been earmarked to upgrade and build rail mass transit systems in major cities and upgrade facilities and buses of local transit agencies, according to the American Road and Transportation Builders Association. The act also provides billions to build and maintain highways, railroads, airports, and waterways.

Challenge #2: Collecting The Right Information Efficiently and Cost-Effectively

Cities are full of potential data sources, from red light cameras to CCTV cameras, but finding ways to efficiently, legally and cost-effectively collect that data is difficult. Without the right data tools, many transportation planners are stuck with inadequate, infrequently updated sources like household surveys that are conducted at the state and national levels. These surveys are rarely updated, and they tend to focus on high-level trends. Using such broad and often stale data makes it nearly impossible for planners to be proactive about the needs of their specific community’s changing demographics. The data are also typically not specific enough to provide instructive insights for granular geographies, such as individual intersections. Unfortunately, conducting local surveys to obtain the data required is cost-prohibitive for many communities.

Once planners are able to collect data from more varied and up-to-date sources, they can start moving in sync with their community’s needs. According to an article on Geekwire, one way Seattle was able to better analyze and understand bus ridership was using payment cards and sensors to collect more than 20 million individual data points like location, route number and time of boarding. This is a great example of how a city can take advantage of existing data that is already being collected for a different purpose.

By using comprehensive, real-world data instead of relying on intercept or household surveys and then modeling behavior to estimate travel patterns, Seattle was able to create a data set that was truly persuasive to stakeholders. Thanks to this foundational knowledge based on observed trends, the city was able to identify the specific problems that caused the greatest mobility challenges for the largest number of people more effectively. Monitoring the data over time allowed planners to understand trends in bus ridership and move quickly to address the overcrowding issues that would have the greatest impact on user satisfaction.

Challenge #3: Understanding What the Community Truly Needs

Without frequently updated, comprehensive, and accurate data, it’s difficult for transportation planners to get a clear picture of their community and its transportation needs. Using data from the surveys that are five to 10 years old forces transportation planners to be purely reactive or worse — to guess at what the city needs, or respond to the city’s loudest constituents instead of its greatest challenges.

To put it in perspective: the first ridesharing service, Uber, was established in 2009, and the company did not launch its popular “UberX” service, which dramatically expanded its driver base and ridership, until June 2013. It is unquestionable that this service and its competitors have dramatically changed travel behavior, especially in urban areas. However, the last National Household Transportation Survey (NHTS) used data collected from April 2008 – April 2009, before these services were widely available. While an updated NHTS is currently underway, the results have not yet been published.

With many cities like Seattle booming and creating transportation issues that affect residents’ ability to get to work, school, and recreation, planners cannot let negative issues such as congestion impact their city’s economic future. However, evaluating those issues using out-of-date information prevents them from forecasting the impact of infrastructure and policy solutions.

Mobile apps have also transformed the way people access information in their personal lives, and it’s now an expectation that all data will be accessed in real-time. Taking snapshots of real-time data as simple as the number of people boarding a bus empowers transportation planners. Not only can they more effectively allocate resources and create the best routes, they can use that data to better forecast usage and long-term transportation needs. With a growing emphasis on public transportation, a city must have options to meet its residents’ needs. Promising a solution “soon” isn’t going to create the kind of user-friendly options that cities need.

For example, transportation planners are looking at ways to track traffic flow and could use that data to help identify better areas to locate office parks as well as where more capacity is needed for roads and public transportation. Instead of simply adding more lanes or public transportation routes, transportation planners can look at ways to better use their existing resources without the added expense and user impact that construction brings.

Transforming Your Transportation Data Process

By moving to a more accurate, comprehensive, and precise data collection tools, transportation planners can revolutionize the way they collect and analyze transportation data. No longer held back by outdated and inadequate data, transportation planners are now able to be responsive to their community’s evolving needs.

With more powerful forecasting that is informed by real-world data, transportation planners are able to address any potential issues before they become massive problems. With this knowledge, they can also present more realistic budget requests and get the funding they need the first time, instead of making multiple requests, and possibly being denied the full funding they’re seeking.