We’ve added a brand-new type of analysis to StreetLight InSight®: the Segment Analysis. This feature helps you measure corridor travel behavior faster and more comprehensively. In this blog post, we’ll show you how the feature works and walk you through three great ways to use it:
For a live demo of this new feature and more, sign up for our webinar on December 12th.
If you’re like many drivers today, your heart sinks when you see an orange road sign with the word “DETOUR.” Suddenly, you remember the flashing highway sign that warned you in advance that construction was coming. In today’s busy world, you simply forgot and did not prepare. As you join the hundreds of other drivers who are now taking a circuitous journey around much-needed construction, you realize that you’re going to be late.
But with the right data tools, transportation planners can make these frustrating detour experiences much better. When planning major transportation projects such as construction and lane closures, it is essential to identify the best alternate routes to reduce traffic disruption – that’s something we can all understand. But it’s time to change the way we identify them. Learn more about using Big Data to improve detour planning in this blog post.
Get the latest news about Big Data and mobility analytics for the transportation, retail, and real estate industries.
Can’t get enough transportation in your life? Neither can we! Here at StreetLight Data, we’re pretty serious transportation nerds! As we settle down to enjoy the Thanksgiving holiday with our loved ones, we’ve been thinking about all the different transportation-related transportation movies, books, and more that we can enjoy.
Since we're also getting ready for a great webinar on multimodal planning with the City of Toronto (register here!), we’re sharing our top 5 transit-related movies, books, and TV shows in this blog post. Enjoy!
At this point, it seems clear that autonomous vehicles are on the verge of technical feasibility. Just last week, Waymo announced that it is testing self-driving minivans without a human back-up in the front seat. Its employees will be riding in the back with an emergency stop button – but no steering wheel. But do these technical advances mean that we’re ready for AVs? How should we manage the non-technical aspects of AV deployment to ensure they achieve promised improvements in safety and accessibility?
I decided to write this article to address these issues after participating in the Intelligent Transportation System World Congress earlier this month. There were tons of panels focused on autonomous vehicles, and I was lucky enough to be speak on one that dove into the critical questions for civic leaders and transportation professionals. We went beyond technical readiness to ask ourselves if should we deploy AVs, and, if so, how should we deploy them?
Getting the data you need to make savvy transportation planning decisions can be a lengthy, expensive process if you’re using surveys, license plate counts, or road sensors. These methods also make it difficult to evaluate the performance of a policy or project after implementation.
For example, when planners rely on old or modeled data to design their project, they don’t have a real-world baseline to evaluate current performance after a project is completed. Most road sensors are removed after a few days, so they must be re-installed to collect more data. Surveys can take months or even years to complete. If planners want to make performance-based improvements as they implement policy or infrastructure changes, they often have to start from scratch with data collection. This could create real flaws if your community has seasonal variation based on weather or school - or if your community has new transportation patterns derived from the rise of ride share or urban population growth, for example.
In today’s world, there are much more efficient, up-to-date, and accurate ways to obtain the information you need. Nearly 77% of the US population uses a smartphone, and the data they produce is creating new options for transportation planners. In this article, I’ll share four advantages that Big Data has over conventional data sources for transportation planning.
As a San Francisco-based company, the wildfires that recently spread across northern California have been extremely troubling for our team at StreetLight Data. For us, this went beyond poor air quality in the Bay Area. The fires impacted the homes and personal well-being of our employees, our clients, and our families. While it is always difficult to see tragic events occur anywhere in the world, watching fires destroy places we love was something else entirely.
The experience forced us to think harder about what we, as a company, can do to help. Our product, StreetLight InSight®, helps transportation professionals use Big Data from mobile devices to understand travel patterns – but what specific information can it provide to aid in evacuations? At a personal level, how can we help communities in need, at least in the continental US and southern Canada, where we currently operate?
Before I dive into details, I want to stress that we’re here to help. If your community is facing an imminent evacuation, and our Metrics could help you get people get out of harm’s way, email me (I’m the CEO) directly. Tell me what you need, and we’ll skip the formalities and paperwork to provide the data for free as quickly as we can.
Public transit is a key component of cities’ mobility networks, especially in dense urban centers. Trains and buses help commuters avoid the hassle of traffic jams on congested roadways, not to mention pricey parking. But some cities are attracting commuters and residents so quickly that public transit cannot keep up -- just ask anyone who lives in Denver, Colorado.
The population in Denver has grown by ~45% since 1996, and the average commuter there now spends 49 hours per year sitting in traffic, but only 4.4% of commuters use public transit (Source: Denver Post). Similar scenarios are playing out across the US in cities like Austin, Seattle, San Francisco, and more. Even though alternatives to driving are available in many of these growing cities, not enough commuters are using them – and congestion keeps getting worse.
Traditionally, public transit planners improve systems by looking at existing transit users’ behavior. They identify potential users as those who live and work near transit stations. But in this era of rapid urban population growth, we cannot consider these groups alone: What about the people who are driving because transit isn’t currently a viable option? What about the people who could be using the transit to commute, but aren’t? In this blog post, I’ll walk you though a few ways Big Data can help address these questions.
We’re excited to share that StreetLight Data has a new public agency partner: Minnesota Department of Transportation (MnDOT). The agency recently signed up for a one-year pilot of our Regional Subscription to StreetLight InSight®, the first online platform that turns Big Data from mobile devices into transportation Metrics.
MnDOT’s Regional Subscription provides designated users with unlimited access to StreetLight InSight for Metrics in the state of Minnesota (and a buffer area). That means MnDOT’s Regional Subscription users can design and run as many StreetLight InSight transportation studies as desired to during their subscription term – without any incremental costs or additional procurement processes.
We just passed our one-year anniversary of using Location-Based Services (LBS) data, so we decided to update some key sample size figures. The results are exciting: Our sample size has doubled to more than 62 million devices in the US and Canada in the past year. In other words, now our analytics anonymously describe the travel behavior of 23% of the US and Canadian adult population.
There are many reasons for this increase, including our main LBS data partner, Cuebiq, doing a great job. However, the most important reason is that Location-Based Services are becoming more and more widely adopted by consumers. As a result, our clients can now analyze the aggregate travel patterns of nearly ¼ of the population in just a few mouse clicks.
That’s a large sample by any measure, but when you consider the “status quo” methods of collecting travel behavior data, it’s even more dramatic. Imagine how much it would cost – and how long it would take – to collect household travel surveys from 62 million people, or to install sensors and traffic counters on the roads they use every day. It just wouldn’t be feasible. In this blog post, I’ll explain how we calculate sample size (hint: accuracy is more important to us than flashiness) and why it’s grown so much in just one year.
We’re excited to share that StreetLight Data and PTV Group have taken the next step in our partnership: Our first integration of StreetLight Data’s transportation analytics into PTV Visum, one of PTV Group’s flagship software platforms for travel demand modeling. For the first time, transportation professionals can use up-to-date, comprehensive Big Data analytics in their models in just a few mouse clicks.
Our new feature means that modelers do not have to manually process .CSV files or write custom code to use our origin-destination matrices in their Visum models. Instead, they can install the StreetLight Add-In to Visum, then pull in the data they need in a flash. In this article, we’ll explain why we decided to build an integrated data solution for modelers, how it works, and the next steps for our partnership.
Ohio Department of Transportation (ODOT) recently selected StreetLight Data to provide on-demand transportation studies along with one of our partners, INRIX. We’re thrilled to see ODOT join the hundreds of public agencies across the US and Canada that benefit from our Big Data analytics.
The Labor Day public holiday celebrates American workers by giving them the day off – or at least, that’s the idea. Here at StreetLight Data, we wanted to find out how many American workers are still commuting to their jobs on Labor Day. The results were surprising: Only about ~56% of American workers get the day off nationwide, with some variation in results across different states. In this blog post, we’ll walk you through our analysis of Labor Day travel patterns.
Traffic congestion negatively effects the economy, roads and our quality of life. Some people tend to blame pass-through trips, commercial attractions or employers, but expectations don’t always line up with hard data about what really causes congestion.
In California’s Napa County, for example, it is common to blame traffic on wine-tasting tourists. However, when planners used Big Data to map out travel behavior in traffic congestion studies, they found out that commuters actually contributed as much to congestion as tourists. High housing costs in Napa are a major part of the problem.
It’s not easy to figure out why congestion happens, especially in downtown districts. Learn how to improve the accuracy of your traffic congestion studies by using analytics derived from Big Data.
This year, the Eastern Research Group (ERG), Coordinating Research Council (CRC), and StreetLight Data teamed up to validate one of the big as yet unmet promises for Big Data – the ability to better model and thus manage criteria pollutant air emissions from vehicles.
The results of our work show that using Big Data to model emissions at the county level is more accurate than industry-standard practices today. Of three different counties we analyzed, we found that:
Modeling emissions accurately matters: It allows air quality models to better predict concentrations of the regulated air pollutants ground-level ozone and particulate matter in different counties, which informs air quality planning and control strategies at the local level. In this blog post, we will walk you through the new methodology and some of our key findings.
Locational Big Data – the geospatial data created by mobile devices – is ubiquitous. Smartphones, connected cars, fitness trackers, and more create trillions of location records as their users go about their daily lives. There are many benefits of this Big Data, but one, of course, is large sample size. But just knowing something is “large” is not always enough. Many of our clients want to know more detailed info on sample size for individual projects. It helps them understand certainty of results.
In this blog post, I’ll explain how we’ve updated StreetLight InSight® (that's our easy-to-use online platform for transforming Big Data into transportation analytics) so that our clients always know the size of the sample they’re working with.
In my hometown of San Francisco, California I grew up riding the municipal bus home from school with a group of classmates. As a group, we saw the San Francisco Municipal Agency (SFMTA) try a multitude of strategies to make the system more efficient and cost-effective. For example, SFMTA transformed car lanes into dedicated bus rapid transit (BRT) lanes to increase the fleet’s speed. When many of these decisions were made, most of my bus crew was under the voting age, and as teenagers, public forums were not an exciting Friday night activity.
I remember that we complained almost every day about how slow or inefficient the bus was, yet we never did anything to try to fix public transit. We never participated in the public forums or in outreach programs that gathered feedback on BRT. Now, as BRT expands, huge changes are happening to the system that affect my current commute. However, at the same time as SFMTA was inviting the public to share their feedback, I bought a smartphone. To the dismay of my parents, I used that smartphone constantly. Now imagine if my teenage obsession had allowed me to be a more active participant in decisions like the BRT, simply because SFMTA could use the location data created by my phone to develop their future plans.
When it comes to transportation planning, it seems like Big Data—location data created by connected cars and trucks, smartphones, and wearables—is the next big thing. How public agencies will actually use and implement this data is the big question on people’s minds.
With 2.5 quintillion bytes of Big Data being created daily, and much of this data offering valuable insights for transportation planning, it almost seems negligent for government agencies to not use this information source. Brookings Institution, a non-partisan research institute, recently looked into why government agencies are lagging behind on Big Data adoption. With the help of our CEO, Laura Schewel, the Brookings Institution has brought to light the core disconnects between government agencies and Big Data, and some of their findings may surprise you! In this blog post, I’ll take you through our key takeaways from the report.
These days, the shopping mall industry just can’t seem to shake the doom and gloom headlines. According to Business Insider, a “Retail Apocalypse” has officially hit America. While it’s true that declining in-store sales are forcing some retailers to close stores, those headlines don’t tell the full story. Jumping to the conclusion that it’s “the end of the world” for the modern American mall discounts their potential to adapt and thrive in today’s world. Given the socioeconomic impact that shopping centers have on our communities, we should celebrate and encourage their potential to adapt – not discourage it.
At StreetLight, we know how important shopping malls are for our communities, and we’re committed to building the tools they need to thrive. When malls and shopping centers close their doors, towns and cities don’t just lose a place to shop. People lose a place to connect to face-to-face and communities lose employers. Abandoned shopping malls can even become hotspots for petty crime. But that doesn’t have to be the future of the shopping mall.
The successful malls of the future will be those that recognize the changing desires of today’s consumers, then adapt to meet them. In this blog post, we will share a few ways for real estate and shopping center professionals to turn today’s shopping centers into the malls of the future.
I’m thrilled to announce our latest monthly update of StreetLight InSight—that’s our online platform for transforming Big Data into transportation Metrics in minutes. With this release, our platform does even more to close the gap between Big Data and actionable analytics.
We’ve achieved this by adding several new Metrics, updating our databases with the latest location data sets from our suppliers, and implementing features that make StreetLight InSight more user-friendly and responsive. In this blog post, we’ll dive into the most important updates.
Traditional methods of collecting information travel data feel familiar and intuitive to most transportation professionals. That makes sense because household surveys and simple sensors like tube counts have been around for decades. In contrast, Big Data can seem vague and conceptual. (Note: we define “Big Data” as the location records created by mobile devices.) The size and complexity of raw geospatial data sets make it nearly impossible for most transportation professionals to collect and process Big Data on their own.
But as vague and conceptual as Big Data may appear at first, it is actually just as straight-forward as traditional tools if you approach it in the right way. In this blog post, I’ll walk through three key steps that planners can take to use Big Data effectively.
From ride-hailing apps and volatile gas prices to electric cars and (theoretically) autonomous vehicles, transportation behavior is rapidly changing. To properly plan for and manage our evolving transportation system, engineers and planners must keep pace with these changes. If managing transportation demand is important to your community, it’s not enough to follow the old pattern of creating new core analytics every 5-10 years to feed your models for any type of planning. For transportation demand management (TDM), which could be most profoundly affected by these new trends, the need for up-to-date, real, accurate data is even sharper.
In today’s evolving environment, effective TDM requires regular access to clean, up-to-date data. One problem that many planners face is that surveys and other traditional data-gathering methods simply cannot deliver high quality data at a frequent update cadence and affordable price.
Keep reading this blog post to learn all about TDM, and to find out how Big Data can help you maximize the impact of TDM strategies.
It’s undeniable that “Smart Cities” are getting all the buzz these days, especially when it comes to using Big Data for transportation. But it’s not right to leave rural communities out of the conversation. In fact, rural communities stand to reap the same benefits from better travel behavior data as densely populated areas – if not more.
That’s why it’s so upsetting for me to hear this type of comment at industry conferences: “Big Data sounds great. But I know it won’t work in my rural county. There’s not enough coverage.” That’s outdated thinking, plain and simple. It may have been true just a few years ago, but “Big Data” – AKA the billions of location records created by mobile devices every month – is a fast-growing, continually improving resource. With the rise of Location-Based Services (LBS) for smart phones in particular, we’ve seen an explosion of geospatial data sets with excellent coverage in rural areas.
As a Virginia native with family and friends across the many rural areas of the state, this issue hits close to home. I know from our data and my personal experience that rural drivers drive many more miles per day on average than urban drivers. We owe it to these communities to plan transportation systems that account for their unique travel behaviors.
To do that, rural planners need the up-to-date, comprehensive, and precise travel data that is only available from mobile devices. So in this blog post, I’m going to show that Big Data analytics for transportation are in fact widely available and extremely useful for rural areas.
After many years of client requests, we’re releasing the first cut of our StreetLight Volume: 2016 AADT Metric on the StreetLight InSight® platform. These beta Metrics provide a very robust estimate of 2016 Annual Average Daily Traffic (AADT) for almost any road in the US. To learn more, keep reading this blog post, or watch our recorded webinar on the new Metrics. Click here to watch the webinar.
We believe this Metric provides estimates that are comparable or better than most of the standard AADT estimation practices for three reasons:
The more I work with StreetLight Data’s location-based services (LBS) data set, the more I realize that it is the data source the transportation industry has been waiting for – and that it deserves. Over the past few months, LBS data has emerged as a resource with all the benefits of cellular data, but without its limitations. LBS data can answer a huge array of travel questions that fill in the long-standing information gaps for the transportation industry, especially when used in combination with navigation-GPS data.
But since it’s so new, there’s very little information available to planners about its value today. We’re working to correct that with a series of blog posts that zero in on a different aspect of LBS data – and this is the first. In this post, I’ll highlight LBS data’s spatial precision.
Earlier this year, we integrated our new Location-Based Services data source into the StreetLight InSight® platform. Since then, we have steadily introduced Metrics and features built off that data that help our clients glean even more useful information from our platform. In this blog post, I’ll highlight the most exciting developments. (In case you need a refresher, StreetLight InSight is our easy-to-use cloud-based platform for transforming Massive Mobile Data into analytics that describe travel behavior.)
At StreetLight Data, we transform location data from connected vehicles and mobile devices into Metrics that describe travel patterns through our easy-to-use StreetLight InSight® platform. The name StreetLight Data is a metaphor for the light that our analytics shine on mobility behavior. In other words, we don’t do streetlights – or rather, we haven’t before.
Lately, I’ve been thinking a lot about the city of Atlanta, where a fire recently destroyed a portion of the I-85. It’s a major highway that hundreds of thousands of people use every day to access to their jobs, their schools, their groceries, and more. For me, the highway’s closure highlights how vital our transportation networks have become to quality of life in our communities. Even in a best case scenario, residents of the Atlanta region are likely to spend several months without this vital transportation connection – and the typical Atlanta resident already spends more than 70 hours in traffic each year. What can we, the transportation community, do to limit the negative consequences of unforeseen events like this? It's not a simple problem for anyone to solve, and we know that the folks in Atlanta are working day and night to solve it. In this blog post, I will describe a few data-driven tactics for reducing congestion misery on I-85 in Atlanta. We hope that this analysis will be useful for detour management in Atlanta in the coming months.
Note: This is a guest blog post from Wendy Tao, the Head of Business Development and Strategy of the Intelligent Transportation Systems Group at Siemens Mobility. Wendy helps communities develop Smart Cities solutions related to advanced traffic management systems, adaptive signal control, connected vehicles and multi-modal applications.
From Intelligent Transportation Systems (ITS) to Massive Mobile Data, innovative technologies are tackling decades old challenges and creating new opportunities in the transportation industry. And it’s not just an idea. We’re seeing significant impacts derived from in-depth evaluations on project performance and cost-effectiveness. Siemens recently partnered with StreetLight Data to measure the impact of a Siemens’ SCOOT adaptive signal control implementation in Ann Arbor, MI. Our empirical before-and-after study showed that SCOOT can reduce travel times by 10 to 20 percent. The study used archival navigation-GPS data from connected cars.
Transportation planners today face a ton of challenges as they work to build efficient, safe, and sustainable urban transportation systems. From rising congestion to increased demand for public transit, the travel behavior and transportation preferences of modern city dwellers are changing fast. These challenges raise complicated questions for urban transportation planners; for example, “How do we handle the rise of ride hailing apps? If we add more public transit options, will people use them? How do we minimize the impact of construction if we do expand public transit? And how do we pay for all of this?”
When we founded StreetLight Data back in 2011, our sole focus was to help educate and plan for electric vehicles (EVs). But we quickly realized that our transportation analytics would have a more significant positive impact if we expanded our mission. However, EVs are still one of my deep interests: I drove a Chevy Volt for several years before going car-free just a few months ago, and I focused on EVs in my early career at the Rocky Mountain Institute and Federal Energy Regulatory Commission. Based on my personal experience, I know we can do a better job of planning and deploying EV charging infrastructure. If we want to see wide adoption of EVs, then we must make charging more convenient and affordable while minimizing its impact on our electrical grid. Given the wave of new charging station deployments in the US and abroad, now seems like the right time to explain how Big Data can help.
Autonomous vehicles (AVs) are beginning to dominate much of the public conversation about our transportation future. This was certainly the case at South by Southwest, where I participated in an excellent panel discussion at the C3 Smart Mobility Showcase: “Smart Cities and Data-Driven Deployment of Autonomous Vehicles.” Nearly every single panel at the showcase was related to AV technology. People in that tent were very excited about AVs. However, I found myself thinking back to the 12-lane urban highway that my taxi driver took from my hotel to the event. The local bus would have taken over three times as long, and the drive reminded me that AVs are not a panacea for all that ails our transportation system.
Don’t get me wrong: Talking about AVs at an event like SXSW makes sense, and I’m glad we’re having these conversations. But I think the broader discussion around AVs needs to be focused on accountability. The impact of AVs could be very positive or very negative, as many transportation experts have suggested. In this blog post, I’ll explore how a data-driven approach can help us strike the right balance with AVs, and hold ourselves accountable for achieving a positive outcome for all.
The smart city movement’s first wave brought tons of stationary sensors to our cities, especially in the context of transportation. These sensors are passively collecting valuable travel pattern information at traffic lights, parking lots, bus stops, sidewalks, and more. But if we want cities that are truly smart – if we want to solve the challenges exposed by our stationary sensors – we have to go beyond them. In this blog post, I will use New York City as a case study to explain why.
For even the most seasoned consulting firms, winning a government contract through competitive bid is no cakewalk. However, there are ways to make your proposals rise to the top – and today, StreetLight Data is introducing a new way to differentiate with StreetLight InSight®, our easy-to-use online platform for turning Big Data into transportation Metrics. Our new Consultant Subscription allows consultants to customize, visualize and download Metrics derived from Massive Mobile Data in ways designed to help grow their businesses. Keep reading this blog post for all the details.
Two of the questions we’re often asked here at StreetLight Data are: “What percentage of the population is creating the location records in your sample?" and "Does the location data in your sample fairly represent all income groups, or is it biased?” In this blog post, we’re pulling back the curtain on our internal evaluation process with a deep-dive analysis of our newest data source: Location-Based Services data. We started using this data source chiefly because of its large sample size and representativeness, so in this blog post, I will show you our process for determining these characteristics. (Click here to read more about Location-Based Services data in general.)
I’m excited to share that we updated StreetLight InSight® again this week – and it’s an update that I’ve been eagerly anticipating for quite a long time. Beginning now, our clients can access Metrics derived from our new Location-Based Services data source directly from our StreetLight InSight web app – that’s our one-stop, cloud-based platform for the best Big Data resources and the processing software that makes them useful. So, why am I so excited about this? It means some of our most popular Metrics are even more comprehensive and accurate than before. That’s because our device sample size now represents about 10% of the U.S. population. We’re processing roughly 60 billion location data points into travel pattern analytics every month – and counting!
Since Donald Trump's election on November 8th, 2016, we’ve noticed a major uptick in complaints about traffic in his Manhattan neighborhood. That’s no small feat, especially given that New Yorkers are known for complaining about traffic – just ask Jerry Seinfeld. (For the record, we complain about traffic a ton in San Francisco, too.) However, we hesitate to use subjective grumbling to measure the impact of events. Thanks in part to cognitive biases, people have a tendency to exaggerate traffic and other negative events. Since we were curious about exactly how much travel patterns changed in New York after the election, we decided to use Big Data to crunch the numbers ourselves. (Note: Our study originally appeared in USA Today. Click here to read the article.)
At last week’s Transportation Research Board Annual Meeting, I attended an excellent panel discussion about transportation data. Towards the end of the panel, the moderator challenged the group with a somewhat loaded question. I don’t recall the exact phrasing, but it was along these lines: “As transportation professionals, we know that we have a huge amount of work to do to upgrade, maintain, and repair our infrastructure. The backlog of projects that we have not yet begun is overwhelming. Given our clear mandate - and the often politicized process of infrastructure investments - does all this new data actually impact our decisions in the real world?” It’s an important question to ask - but based on audience feedback and in my own opinion, the answer is clearly yes.
Occasionally, when I introduce myself as an employee of StreetLight Data, people ask: “Oh, so you measure the data from streetlights?” We do not do that - yet! (But stay tuned for more information on our new partnership with Current Powered by GE down the road)
We're beginning to hear this question often enough that we wanted to publish a blog post about our name. And now is the right time to tell our story: Next week, we will be exhibiting at the Transportation Research Board Annual Meeting, and the StreetLight Data booth (#639) is located near a traffic signal manufacturer.
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 effecient 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.
A few weeks ago, one of my best friends from graduate school moved to Colorado to work for my old employer, Rocky Mountain Institute. It’s a nonprofit research and educational foundation dedicated to efficient and sustainable use of resources. The downside – from my perspective – is that he and his equally awesome wife moved to Boulder, CO for this job. The upside – from his perspective – is that now he can go skiing every weekend. The question is: where should he go skiing?
External trip estimation is one of the most important measures for planning departments across the country. Like all kinds of travel, external trips cause wear and tear on local roads and contribute to traffic jams. But unlike your local residents, drivers simply passing through your community don’t contribute to your local economy. They’re not stopping to eat or shop. In this blog post, we've identified 10 ways that these trips can impact transportation planning in your community.
Ever since we launched StreetLight InSight, our transportation clients have asked about scaling the StreetLight Trip Index to estimate actual vehicle trip counts. Our recommendation has always been to do this manually using trusted local calibration data. In yesterday’s StreetLight InSight update, we transformed that manual process into an automated one with our new, BETA calibration feature.
This means that if you have average daily travel data that you trust for roads that are nearby (or even within) your project, you can enter that information directly into StreetLight InSight and automatically scale Metrics to estimated counts.
When I realized that 70% of our team would be traveling somewhere besides their own home on Thanksgiving Day this year, I found myself wondering: “Is this typical?” So, to find out just how dramatically Americans’ travel patterns change during holidays, we analyzed nearly 300 million personal trips that took place in the US from September 2015 to December 2015. We used our algorithmic data processing engine, RouteScience® and navigational GPS data from our partner INRIX to drill down on the volume and length of trips that occurred on holidays as compared to trips on more typical days. Keep reading to find out what we learned.
In this post, we explore using Big Data for detour planning using StreetLight InSight®, our easy-to-use web application for transforming Big Data from mobile devices into transportation Metrics. We analyzed the Race Street Bridge in Lehigh Valley, Pennsylvania because that region’s planning commission intends to spend nearly $183 million USD upgrading 30+ bridges in the next four years – including this one. Because of the FAST Act, communities like Lehigh Valley can now more easily tap federal funds for much-needed repairs.
Here at StreetLight Data, we have high standards for data science because it is the backbone of our product and value proposition. Ironically, we also suspect that anyone who holds the job title “Data Scientist” may be overpaid: At its core, good data science comes from good engineering. As one of StreetLight Data’s co-founders and its Chief Technology Officer, I’ll dive into StreetLight Data’s approach to data science in this blog post.
Transportation planning has always been an important task of local government. Improving community accessibility, safety, and health are just some of the objectives. But external trip estimation is a facet of planning that’s often overlooked, especially by small- and medium-sized communities.
However, pass-through trips (also called external-external trips or external trips) are a trip type that may make up a large portion of travel in your municipality.
Since I joined StreetLight Data as VP of Sales and Services just a few weeks ago, I’ve found myself energized by both team I have joined and the product we provide, StreetLight InSight®. But I can’t deny the flicker of apprehension that I felt right before my first day. Change is not always easy: I previously worked for more than 10 years at Autodesk, where I helped build global sales teams, established the company in new industries, and brought brand-new products to market. From my clients to my colleagues, the Autodesk community still
feels like family to me – and I’m proud of that.
We're thrilled to share that StreetLight Data has teamed up with PTV Group, a transportation modeling and forecasting software provider. As Laura Schewel announced at PTV's North American User Group Meeting this morning, PTV plans to integrate StreetLight Data’s Travel Metrics into its Visum, Vissim, and Vistro modeling tools. We'll discussed the details during a webinar on November 2nd at 10am PT. Click here to watch the webinar recording.
We're excited to share that StreetLight Data's CEO, Laura Schewel, will be speaking at the Annual Meeting of the Virginia Municipal League on Monday, October 10th. She was invited to speak at the conference because of StreetLight Data's extensive work across the state, especially in Northern Virginia. To learn more about the analytics that StreetLight has developed about travel patterns in Virginia, click here to read our case study on transportation demand management.
At StreetLight Data, we’re always updating StreetLight InSight, our easy-to-use web application for transforming Big Data from mobile devices into Metrics that describe travel patterns. (Not familiar with StreetLight InSight? Click here to sign up for our monthly introductory webinar.) Typically, our usability enhancements have focused on improving StreetLight InSight for individuals. In our last two monthly releases, we took a different approach: Optimizing StreetLight InSight for large projects and large teams. In this blog post, we’ll share the highlights.
I’m excited to share that StreetLight Data has officially announced its new data partnership with Cuebiq, a next generation location intelligence company. As a result of this partnership, StreetLight’s total device sample size will increase to more than 30M devices – that represents over 10% of the adult US population.
In this blog post, we highlight how to use Big Data to measure the performance of transportation policies and infrastructure projects. Since we’re deeply concerned by the rise in traffic fatalities in 2015, we decided to evaluate the performance of a popular safety measure: a road diet.
Will you be attending the TRB Tools of the Trade conference in Charleston, South Carolina next week? If so, we look forward to seeing you there!
Stop by our booth to learn more about StreetLight InSight®, our easy-to-use web app that transforms Big Data from mobile devices into Metrics such as origin-destination matrices, select link studies, and more.
As someone who has worked in transportation for my entire career, I was angry and upset when I learned US traffic fatalities in 2015 rose by 7.2%. These statistics show that, despite tremendous innovation in mobility technology in the past year – from automated vehicle testing to new materials to ridesharing to electrification – we are failing to make America’s roads safer for pedestrians, cyclists, and drivers alike.
In response, US Secretary of Transportation Anthony Foxx has issued a powerful call-to-action: “Despite decades of safety improvements, far too many people are killed on our nation’s roads every year. Solving this problem will take teamwork, so we’re issuing a call to action and asking researchers, safety experts, data scientists, and the public to analyze the fatality data and help find ways to prevent these tragedies.” When I heard his call-to-action, I knew immediately that StreetLight Data would take part.
In this blog post, StreetLight Data’s Kim Harrison uses StreetLight InSight®, our easy-to-use web app that transforms Big Data into useful transportation analyses, to evaluate the causes of congestion on her morning commute from Walnut Creek, CA to San Francisco, CA.
At StreetLight Data, we’re excited that Vehicle Miles Traveled (VMT) is gaining traction as a transportation performance measure. In this blog post, we explore the reasons behind increasing interest in VMT and discuss why StreetLight InSight®, our easy-to-use web app for transportation Metrics, is a great tool for calculating and exploring VMT. If you’re not familiar with StreetLight InSight, click here to learn more by watching our demo videos.
Are you attending the Institute of Transportation Engineers Annual Meeting in Anaheim, CA this week? Come meet our CEO, Laura Schewel, at the event.
Laura will be discussing a joint project that StreetLight conducted with Siemens and the City of Ann Arbor: Using an Ecosystem of Smart Technology to Improve Traffic Performance: The Case Study of Ann Arbor, Michigan.
Laura will be joined by Wendy Tao of Siemens to discuss the project from 9:30am to 10:30 in the Marquis Ballroom on August 16th, 2016. Luke Liu and Kevin Braun from City of Ann Arbor also contributed to the poster.
We're excited to share big news this morning: StreetLight Data just launched a new Regional Subscription to StreetLight InSight®, our easy-to-use web app that transforms Big Data into useful mobility Metrics for transportation projects. Our new Regional Subscription offers unlimited StreetLight InSight analyses for one fixed price during the entire subscription period.
StreetLight InSight creates analyses of real-world travel patterns such as origin-destination matrices and select link studies in a matter of minutes. It's available for transportation agencies like DOTs and MPOs - as well as to the consultants and contractors that work with them.
The StreetLight Data team was fortunate to have Tatham Dees join us as an intern this summer. Interested in what he learned and how he contributed? Keep reading this post, which is based on an interview with Tatham about his experience.
At StreetLight Data, we transform trillions of geospatial data points into useful information about mobility behavior. One of the most common questions we’re asked is, “So, where do those trillions of data points come from?” For all of our StreetLight InSight® Travel Metrics as well as many of our Retail Metrics, the answer is “GPS devices.” In this blog post, we’ll discuss the different types of devices that generate the GPS data we use.
Last night, we completed our monthly update of StreetLight InSight – that’s our easy-to-use web app for generating mobility Metrics in minutes. StreetLight InSight Metrics are based on Big Data from millions of mobile devices, and they’re ideal for transportation planning, commercial real estate development, retail site selection, and more. If you’re not familiar with our web app, watch our demo videos or request a 1:1 consultation with one of our Big Data experts to learn more.
StreetLight Data’s CEO, Laura Schewel, will be speaking at the Association for Commuter Transportation's (ACT) International Conference 2016 as part of a panel discussion on "Bringing Extraordinary Data to Your Everyday Work."
When I joined StreetLight Data, I learned that household transportation surveys – that’s physical pieces of paper mailed to residences – are one of the most popular transportation data collection methods. According to my new hire training, these studies can be problematic: they’re difficult to design, the sample sizes are small, and their accuracy depends on the memories of survey respondents. In fact, our product, StreetLight InSight®, was created in part to fill these studies' gaps with locational data from mobile devices.
Serendipitously, the city of San Francisco sent me a survey (see below) on my transportation behavior soon after I joined the team, which gave me the chance to put my colleagues’ claims about household surveys’ flaws to the test.
We’re excited to share that StreetLight Data’s easy-to-use web app, StreetLight InSight, was updated last night. StreetLight InSight generates accurate, precise, and comprehensive Metrics that describe how communities move in minutes. It now features a new type of Travel Metric, faster retail map rendering, and more.
In this blog post, we’re sharing our approach for updating StreetLight InSight and detailing a few of the features in our latest release. If you’re not familiar with StreetLight InSight, check out our demo videos or request a free, 1:1 demo with a StreetLight Data consultant.
Bike shares are riding a wave of popularity in the intermodal transit planning community. They are great because they help address several hot-button urban challenges simultaneously; for example, congestion, air pollution, “last mile” transit gaps, and even sedentary lifestyles. From 2004 to 2015, the number of bike share systems worldwide grew from 14 to 855 – that’s over 6,000% growth!1
However, there are still only 54 bike share systems1 across America’s 486 urbanized areas.2 That means there is plenty of room for expansion in the U.S. We wanted to find out how Big Data could play a role in this expansion.
Sample size is not a simple concept when it comes to Massive Mobile Data Analytics - see our prior blog post for some examples. In this post, we're analyzing our commercial vehicle data’s sample size in California based on a Daily Trip Sample Ratio. The results are that our archival data captures ~11.8% of commercial vehicle trips that took place in California in 2015.
When I visited Austin, Texas for the Women in Transportation Annual Summit, I moderated a great panel on “What is Big Data Really Good For?” This post highlights the most useful insights from our discussion, and is meant to be a quick guide for transportation planners interested using Big Data. My favorite insight: Use Big Data when doing so means spending LESS time collecting data and MORE time optimizing transportation plans for your community.
Thanks to these panelists for the phenomenal work they did to answer the question of the day:
In the transportation industry, we love to debate the optimal sample size for data collection. But this deceptively simple concept can be tricky.
FASTLANE grants are due today – and we’re sharing three data-driven techniques to spend those dollars effectively once you win them. 1) Measure local freight movements before you break ground to design well; 2) Measure shifting freight patterns as you go to mitigate the impact of construction and show achievement of goals and 3) Measure all your peers to see how you’re doing, share your insights, and learn from other best practices.
According to the DOT’s "Beyond Traffic" trends report, US freight will increase by 45% in the next 30 years! Addressing bottlenecks that constrain freight movement is critical and that’s why DOT pushed for the Fostering Advancements in Shipping and Transportation for Long-term Achievement of National Efficiencies (FASTLANE) grant projects. FASTLANE funds transformative significant projects for highway, rail, port, and intermodal freight projects with a size in excess of $100M.
A major strength of Massive Mobile Data Analytics is that it's, well, massive, and we can easily “scan” across large geographies to identify specific patterns of actual travel behavior. To leverage this, we scanned every kilometer in California for truck stops throughout 2015 -- and found some fascinating patterns about the movement of these big (and medium) rigs throughout the state.
Here at StreetLight, we provide analytics for many projects aimed at analyzing commercial and freight vehicles. We support improved freight demand modeling, analyze internal/external routes, explore how trucks going freight hubs like ports move through cities, etc. See our blog for more use cases.
StreetLight Data today is very happy to announce that we have secured $7.5M in Series B financing. In the past year, we’ve seen enormous uptake of StreetLight InSight® by the leading firms working with states, regions, and cities to transform the process of planning infrastructure, and to make the concept of Smart Cities a reality. The potential savings generated by these entities using StreetLight InSight – in terms of time, money, greenhouse gas and criteria air emissions – are substantial. Our new investment will allow us to take our technology, our ideas and our mission so much further, including expanding to new verticals.
This blog post was co-authored with Eric Sunquist of the Smart Transportation Initiative.
In 2012, researchers at MIT and the University of California-Berkeley found that strategic removal of relatively few motor vehicle trips could greatly alleviate congestion. Their method relied on “big data” to determine origins, destinations and routes of travel.
This analysis was done in conjunction with our friends at MotionLoft. Thanks to them and to the team at Great Wall of Oakland. Also thanks to Ozumo restaurant and The Broadway Grand apartments for donating the location and powersource for the Motionloft sensors.
A huge thanks to those who participated in our workshop, especially lead organizer Stephen Crim from MobilityLabs, as well as Tien Tien Chan from the City of Austin, Eric Sundquist from SSTI, Ron Milam from Fehr and Peers, Amy Smith from Uber, Michael Eichler and Justin Antos from the Washington Metropolitan Area Transit Authority (WMATA), and Benito Omar Perez and Laura Richards from the District Department of Transportation (DDOT)
This blog is a recap of a presentation with the same title that StreetLight CEO Laura Schewel gave at TRB 2016. Thanks to TRB and Don Ludlow at CPCS Transcom for organizing the great panel, and to co-panelists Daniel Morgan from US DOT and Peeter Kivestu from Teradata for their excellent presentations.
TRB is a great place to learn and talk about all the big things happening in Transportation, and StreetLight Data is proud to be on a panel that dicusses the use of Big Data in Freight Transporation.
In the vast majority of discussions about Big Data, “real-time” is assumed. Directions based on current traffic conditions. Mobile ads geo-targeted to your specific location and shopping profile right now. On-demand services such as Uber, Postmates, PeaPod, Google Express and more (car sharing, food delivery, etc.) are now a the tip of your finger arriving in minutes. The applications are short-lead time decisions that often have a low value per decision; serving up an ad can cost as little as a few cents.
TRB is a great place to learn and talk about all the big things happening in Transportation, and StreetLight Data is proud to have helped design and organize a workshop tailor made to answer questions about the applications of Big Data in the transportation industry: "Bringing Extraordinary Data to Your Everyday Work."
Part of StreetLight Data’s mission is to “help reduce greenhouse gas emissions and petroleum use in vehicles, especially by reducing miles driven” through the pioneering use of massive mobile data analytics. Vehicle miles traveled, or VMT, is widely recognized as a critical factor for understanding, and thus managing, a variety of negative transportation impacts.
What's driving your county's vehicles miles traveled? In a recent report, StreetLight used its proprietary Route Science® technology to create the trips and run the analyses. First, we received data from a variety of GPS Mobile devices from our partner INRIX. These devices include a mix of smart phones with locational services, cars with navigation systems, trucks with commercial fleet management devices, and more. We used data from four months in 2014 and 2015, one in each season (February 2015, April, June, September 2014).
New York City's Department of Transportation (DOT) unfolded a plan to improve transportation data, which could considerably enhance the ability for NYC drivers to navigate the city safely. Referred to as the Drive Smart pilot program, it collects data directly from individual vehicles, accumulating the most accurate and up-to-date transportation data possible.
The International Transport Forum Corporate Partnership Board's Workshop entitled “ITF Corporate Partnership Board Workshop: 21st Century Public Interest Data Sharing”, will be held on Nov 9 - 10 2015, at the OECD/IEA Conference Centre in Paris, France.
Northern Virginia (NOVA) has tremendous traffic congestion, but limited room to expand highways. The state and local governments want to expand and enhance the suite of Transportation Demand Management programs and investments to reduce travel demand on the highways through approaches like carpooling, transit, bike, and more.
With the change in shopper travel patterns, retailers can no longer assume that trade areas are based on who lives nearby to a store or center. It’s time for them to change their thinking and use advanced analytics to make better-informed decisions.
A few weeks ago, we partnered up with INRIX for a webinar related to data-drive approaches to transportation demand management.
We applied techniques developed at StreetLight Data to create a consistent and comparable measure of “Just Passing Through” trips for every county in the contiguous US. We analyzed nearly 10 million trips that touched any county in the lower 48. Then, we characterized the starting point and ending point of each trip as either inside or outside the county. This allowed us to analyze how many trips were internal, external, or in/outbound to each county. To read the full report, click here.
Today, the Administration is announcing a new “Smart Cities” Initiative that will invest over $160 million in federal research and leverage more than 25 new technology collaborations to help local communities tackle key challenges such as reducing traffic congestion, fighting crime, fostering economic growth, managing the effects of a changing climate, and improving the delivery of city services. "
Here at StreetLight, we're constantly awed by the sheer magnitude of the Big Data Mobile Analytics that we do. We just passed the mark of processing trips representing nearly 50 billion vehicle miles traveled (VMT). This data comes from devices like connected cars, smart phones and commercial fleet management systems.
In a webinar on September 22nd, StreetLight Data and partner INRIX will explain how to apply Big Data to Transportation Demand Management to help with faster, more informed decision making and planning
We applied techniques developed at StreetLight Data to create a consistent and comparable measure of “Just Passing Through” trips for every county in the contiguous US .
StreetLight Data is publishing a series of blogs and eBooks about national transportation trends, based on running StreetLight InSight® Metrics across the country.
Moving Ahead for Progress in the 21st Century, or MAP-21 to its friends, is a major highway bill from 2012. Several clients have asked us recently how StreetLight Metrics can be used for MAP-21-related goals, so we've collected our thoughts in this blog.
Intalytics and StreetLight Data announced that they have entered into an enhanced partnership to enable Intalytics to further leverage the StreetLight InSight® product suite.
StreetLight's CEO, Laura Schewel, recently spoke at two events on how big data analytics was helping to change the retail industry. The International Council of Shopping Centers event was held on August 6th and Laura focused on the best and worst ways to use Big Data in shopping centers. Our partner, Forum Analytics, held their customer summit on August 10th - 12th, where Laura spoke on ways organizations can utilize Big Data in retail.
When you drive to the grocery store do you consider the effects it has on our environment?
At a TedXTalk in Sacramento on Saturday March 7, 2015 our CEO, Laura Schewel, advocated for the smart use of Big Data to transform how we drive and move forward in green transportation.
Traditionally, collecting data on traffic patterns has been hard to do. This article discusses some of the standard methods employed by transportation engineers and planners to better understand travel behavior, in particular, internal and external flows in a city or region.
Forum Analytics, LLC, the Chicago-based provider of business intelligence solutions for enterprise real estate planning, and StreetLight Data, supplier of analytics and insights derived from anonymous mobile devices measuring consumer mobility patterns, announced today they have entered into a partnership.
StreetLight's CEO, Laura Schewel, spoke at the International Council of Shopping Centers on August 6th to share her knowledge on Big Data's effects on shopping centers. She discussed the best and worst ways to use Massive Mobile Analytics. StreetLight also shared how they've used these analytics to determine behavioral trends across the nation. >Learn more<
For Transportation and Urban Planning, the phrase “Big Data” can mean a variety of things. Today, we’re talking about Big Data that is gathered from hundreds of millions of mobile devices across the US, such as smart phones, connected cars, and wearables, and that are used to measure mobility patterns. We call this “Massive Mobile Data Analytics.”
For Transportation and Urban Planning, the phrase “Big Data” can mean a variety of things. Today, we’re talking about Big Data that is gathered from hundreds of millions of mobile devices across the US, such as smart phones, connected cars, and wearables, and that are used to measure mobility patterns.
StreetLight InSight® for Transportation and Urban Planning allows transportation engineers, urban planners, and other professionals to analyze the characteristics of cars and trucks who pass through, stop at, or go to nearly any location in the U.S. and Canada. StreetLight InSight® integrates data from over 100 million mobile devices—cell phones, connected cars, GPS navigation apps, wearables and more—with dozens of additional sources of spatial and statistical information.
With such big advancements in available technology, it’s becoming easier to measure how people and vehicles move around the world. But, what exactly is the data you’re gathering and what should you do with it?
451 Research profiled StreetLight Data for an "impact" report. A summary can be found here. Subscribers to 451 can get the full report as well. Says Rich Karpinski:
Drivers in Northern Virginia can look forward to spending less time in traffic thanks to Big Data Analytics.
Fehr & Peers has published an excellent and detailed project report here. They did all the work involved in the validation. We have merely summarized the results most relevant to StreetLight validation questions below.
"A Note from StreetLight: We are starting a series of blogs on the theme of "data validation." Since StreetLight measures behaviors that are generally hard to measure, it presents a challenge for validation (what's the baseline?). We are collecting cases where good baseline data is available and publishing our findings. If you have suggestions for future editions of the validation blog please get in touch! We're very glad to have a guest blogger, Dave Chipman from Men's Wearhouse, for our initial post. ~Laura Schewel, CEO of StreetLight
StreetLight's CEO, Laura Schewel, will present at STI PopStats 2015 . PopStats is one of the best places for retailers and real estate professionals interested in deep analytics to come together.
On December 8th, The 2014 Siemens Innovators Lounge will celebrate the conclusion of this year's Siemens Competition. Hosted by CNN anchor Fredricka Whitfield, the event will bring together distinguished thought leaders across sectors. Joining StreetLight CEO Laura Schewel on the panel will be Chris Anderson, CEO of 3D Robots, Sunil Gupta, CEO of RISE, and Jessica Jackley, CEO of KIVA.
I just wrapped up a few days at the always-impressive VERGE Conference. This post summarizes the most important messages I drew from a panel discussion including StreetLight Data, StreetWize, and the City of San Francisco’s Neighborhood Empowerment Network.
On October 27 - 30, the annual VERGE SF conference will return to San Francisco. Producted by GreenBiz Group, the event focuses on how the intersection of energy, information, building and transportation technologies is accelerating innovation and creating new product, services and business models.
In a recent conversation with Max Sheets, VP of Real Estate at Freddy's Frozen Custard & Steakburgers, he explained how his perspective has changed during his more than 30 year career in the retail real estate business. Freddy’s, based in Wichita, KS, is a 12 year old fast-casual restaurant chain that has over 120 stores in more than 20 states and is growing rapidly.
I spent several days with the vanguard of commercial real estate analytics at the ICSC Research Connection event this week. Collectively, we circled around the fundamental issue of interest: how do we keep brick-and-mortar shopping centers vibrant? For reasons outlined elsewhere on our site, StreetLight firmly believes that brick-and-mortar shopping is a critical part of strong economies and happy, connected communities.
The International Council of Shopping Centers (ICSC) is holding it's annual Research Connections Conference next week in Denver, CO on September 28th - 30th. The premier event for the intersection of retail, real estate and research, the event will be attended by retailers, landlords, and other industry advisers from across the country.
This week, the 6th annual EcoDistricts Summit, will converge on Washington, DC on September 24 - 26th. The summit will explore district-scale sustainable development and dig deep into the public-private-civic partnerships that are laying the groundwork for the neighborhoods of the future: resilient, vibrant, resource-efficient and just.
When thinking about store trade areas, 16 years is a long time. I found this chestnut - Retail Trade Area Analysis: Concepts and New Aproaches - in Directions Magazine, from that many years ago. To understand where things were at then and how far they how they have come, a little history is in order.
Sponsored by GreenBiz, the Verge Salon 2014 on September 16th is focusing on next-gen Buildings and Cities. StreetLight's CEO, Laura Schewel, will be speaking on a panel titled "Democratizing Data: How to Make it Accessible and Useful".
The online magazine ReadWrite recently published an article "How Big Data Reveals the Secret Life of Cities".
Watch the video below to see commentary by a panel of technology experts and executives as well as Laura's final presentation.
July 23rd, StreetLight CEO Laura Schewel will speak at Deep Dive: Analytics, an event hosted by the Telecom Council of Silicon Valley.
At the Silicon Valley Open Innovation Challenge Culmination Event on July 2nd, Nokia Networks recognized StreetLight Data as the ‘Most Promising Startup’ among seven finalists, selected from an initial group of 90 applicants. As a finalist, StreetLight benefited from personal mentorship by a Nokia ‘Innovation Champion’ as well as from collaboration with Nokia decision makers at a hands-on technical workshop. The Open Innovation Challenge concluded with a grand event where StreetLight presented before an audience of 125 executives, venture capitalists, consultants, and more.
Laura Schewel is participating at European Council for an Energy Efficient Economy summer study this week as part of Transportation Panel. She'll be laying out part of the policy and efficiency context behind the need for much better transportation data collection, that gives some insight into VVCo's future interests beyond EVs. She'll also be learning about EU practices in data collection, EVs, and transportation panel. Watch her twitter feed (@VV_Laura) for the most fascinating tidbits.
StreetLight Data CEO Laura Schewel will be a featured panelist at the upcoming MIT Technology Review Digital Summit: Innovations and Ideas Fueling Our Connected World being held on June 9 - 10 in San Francisco.
StreetLight Data is pleased to announced the company has been selected as one of Red Herring's Top 100 companies in North America.
StreetLight Data and Fehr & Peers teamed up to provide analytics to The San Diego Association of Governments (SANDAG), the regional planning agency in San Diego County. In 2012, SANDAG acquired the South Bay Expressway, a private toll-road running north-south along the eastern side of the region.
StreetLight Data is excited to announce the company has been selected as a finalist for Red Herring's 2014 Top 100 North America award, a list honoring the year’s most promising private technology ventures from the North American business region.
Coming up on May 2 - 3, The Centre for Spatial Law and Policy based in Washington, DC, the Center for Geographic Analysis, the Belfer Center for Science and International Affairs and the Berkman Center for Internet and Society at Harvard University are co-hosting a conference titled "Creating the Policy and Legal Framework for a Location–Enabled Society".
StreetLight Data is pleased to announce that our VP of Strategic Partners and Privacy, Kara Selke, has become a Privacy by Design Ambassador. Kara was one of StreetLight's earliest employees and has helped the company incorporate the 7 Foundational Principles of Privacy by Design best practices into its operations and product offerings.
Travel behavior associated with commercial office buildings has far-reaching environmental, health and business impacts. Under many circumstances, occupant and visitor travel constitute the largest single contributor to environmental impacts of commercial office buildings.
The US Green Building Council (USGBC) and StreetLight Data teamed up over the past year to study the use of aggregated, anonymous cellular data in characterizing commuting distances. The goals of the study were to understand how such cellular data could augment current tools and provide new insights that can guide future green office building certification standards and help companies improve commuting experiences for their employees.
StreetLight Data and the US Green Building Council (USGBC) recently completed a study on the use of aggregated, anonymous cellular data in characterizing commuting distances.
Fehr & Peers, a premier transportation planning and traffic engineering firm, recently completed a travel behavior study of Napa County in California, using StreetLight Data metrics as a key part of its analysis.
Veggie Grill, the entirely plant-based fast casual restaurant concept committed to revolutionizing the way people think about vegetarian food, is growing fast.
StreetLight Data's founder and CEO, Laura Schewel, will be speaking at the upcoming Big Data: Analytics & Driving Innovation event hosted by the AutoTech Council on December 13, 2013 in Sunnyvale, CA.
Earlier in October, StreetLight CEO Laura Schewel participated in the annual EmTech MIT event - "The Conference on Emerging Technologies That Matter" - hosted by MIT Technology Review. Laura was honored as one of Technology Review's Innovators Under 35 and also participated in a panel discussing the future of Connected Cities.
How far can we take the concept and the value of Smart Cities? Are there limits?
StreetLight co-founder and CEO Laura Schewel will be speaking at the upcoming VERGE conference in San Francisco, October 14 - 17.
On October 9 - 11, 2013, MIT Technology Review will be hosting its annual EmTech event -- "The Conference on Emerging Technologies That Matter".
The Telecom Council of Silicon Valley hosted its annual TC3 summit on September 18 - 19, 2013. The premier telecom innovation event of the year, the summit brought together telecom companies who build the communication networks with those companies inventing the next generation of technologies.
On October 2nd, StreetLight CEO, Laura Schewel, will be a panelist at an event focused on connected cars and big data hosted by The Hive. The panel will also feature speakers from Uber, Streetline, Ford Motor Company, and Telefonica. The event seeks to explore the future of connected cars and answer three key questions: what is possible now, what does the future hold and what are the new economics and likely use cases of the connected car.
Today MIT Technology Review reveals its list of 35 top young innovators (https://www.technologyreview.com/lists/innovators-under-35/2013/). For over a decade, the global media company has recognized a list of exceptionally talented technologists whose work has great potential to transform the world.
StreetLight is excited to partner with Predictive Analytics consulting firm Intalytics. By combining StreetLight’s proprietary location metrics with their existing analytics tools, the experts at Intalytics are now equipped with new actionable insights to help their clients make smart real estate decisions.
We are pleased to announce that StreetLight Data's CEO, Laura Schewel, is the winner of the International Transport Forum’s 2013 Young Researcher of the Year Award. Laura was chosen for her paper “Shop ‘Till we drop: A History and Policy Analysis of Retail Goods Movement”, which came out of her dissertation work at US Berkeley.
This is the second post in a series about "Privacy Week" at the IAPP Europe Data Protection Intensive 2013. Read my initial thoughts here.
We are here this week at the IAPP Europe Data Protection Intensive 2013. Yesterday we participated in an interactive session, entitled “How to Build a Global Privacy Programme.” It was filled with interesting and dynamic conversations between privacy professionals from around the world.
MIT Technology Review covered StreetLight and how our data supports new ways of understanding and improving city planning, economic development, and retail strategy.
StreetLight Data today announced that it has secured a seven-figure Euro funding in Series A financing. StreetLight is an innovator in next generation geospatial business intelligence for the in-store retail ecosystem. StreetLight repurposes and recombines data from traffic and transportation management systems (such as traffic jam alerts and navigation) to help retailers better understand the context in which their stores operate. This intelligence can lead to improved site selection, as well as other applications.
Oakland Business Development Corporation (OBDC) has a mission to increase economic activity and opportunity in the City of Oakland. The organization, founded in 1979, has played an important role in helping boost the city over the past 30 years.
Partnership between StreetLight Data and AirSage™ delivers consumer movement and behavior data to brick-and-mortar enterprises.
StreetLight Data will be one of 7 companies participating in the Big Data Start-Up Pitch session at the Global Big Data Conference on Monday, January, 28th at the Santa Clara Convention Center. If you're at the conference, make sure to stop by this session and cheer on our CEO Laura Schewel.
After co-winning IBM's SmartCamp North America regionals in June 2012, StreetLight will now compete for the title of IBM Global Entrepreneur of the Year! On Feb 5 - 7, 2013, StreetLight will join 7 other companies from around the world for an action packed few days in NYC.
This month, Environmental Science & Technology, the top ranked peer-reviewed journal in environmental sciences and policy review, published founder Laura Schewel's new article about changes in how Americans drive to go shopping over the past 40 years. A few highlights:
StreetLight was featured in the IBM Blog as a Smart Camp Winner Spotlight. Check out this interview with Founder and CEO Laura Schewel. We've put a preview below:
StreetLight is thrilled to announce that we were named IBM's SmartCamp Boston, the North American finals for IBM's SmartCamp program for start-ups. StreetLight looks forward to working with IBM on developing projects to create smarter cities, smarter commerce and smarter presentation. For IBM's press release, keep on reading!
On May 24, StreetLight Data was named the winner of IBM's 2012 SmartCamp NYC for Smart Cities. This is part of IBM'sSmarter Planet initiative. StreetLight will go on to compete in Boston next month for the title of North American Entrepreneur of the year. Previous winners in the IBM Smart Camp program include great companies like StreetLine, Profitero, Bit Carrier, and more.
On April 18th, StreetLight CEO Laura Schewel will be speaking at a Telecom Council sponsored lunch meeting on making cities smarter.
StreetLight's CTO Paul Friedman talks about system architecture at The Node summit for The Cube on Silicon Angle TV.
Virtual Vehicle Co has changed its name to StreetLight Data. The name change reflects the expansion of StreetLight's business from advanced vehicles only to broad roadway transportation optimization and location analytics.
Fast Company covered Virtual Vehicle Co on its Virtual Test Drive app and interviewed founder Laura Schewel in this piece. Fast Company writes:
In this series of presentations from the first five of GigaOM Green:Net 10 Big Ideas, Laura Schewel presents a three minute introduction to Virtual Vehicle Co. (Starts at minute 14:00)
Virtual Vehicle Co. has been selected by the smart folks at GigaOM as one of 2011's BIG IDEAS bringing together clean technology and information technology.