In the United States, a transportation safety crisis is leading to record numbers of fatalities: 38,680 people were killed in motor vehicle crashes in 2020, and by the end of 2021, nearly 43,000 more people had died on U.S. roads, marking a 10.5% overall increase in deaths — and the highest death toll recorded since 2005.
Among these fatalities, about 13% were pedestrians — that’s 7,388 people who died while walking, the highest number recorded in decades.
At the same time, the rate of fatalities per 100 million vehicle miles traveled (VMT) has also worsened, increasing significantly in 2020, likely due to high rates of speeding during early COVID lockdowns that led to empty streets. But this increase held steady in 2021.1
Faced with these fatal statistics, the need for safer roadway infrastructure is clear. To address the problem, transportation professionals must diagnose the factors that make roads so fatal and implement countermeasures that are proven to work. But not every road needs the same safety improvements. So how do you ensure safe transportation infrastructure?
In this post, we’ll examine:
What makes public roads safer for various modes of travel
The Safe System Approach to transportation safety
Ways to improve transportation infrastructure safety
The data behind safer infrastructure
What Makes Roads Safe for Each Mode of Travel?
There is no single factor that makes all roads safer or more equitable. Each road and mode of travel may benefit from different types of infrastructure and policy, making a data-informed approach key to effective safety interventions.
It should be acknowledged that non-infrastructural factors — such as vehicle design and driver education — also impact road safety and should be considered as part of a holistic approach to reducing fatalities and injuries on the road.
However, in this article, we’ll focus specifically on transportation infrastructure and road design strategies that boost transportation safety. Below, we’ll explore some of the ways you can make public roads safer for various modes of travel.
Public Transport Safety
Public transport safety has to address a couple of overarching concerns: First, modes of public transportation, like city buses or streetcars, need safe roadways. Second, access points like bus stops must give riders safe ways to wait, embark, and disembark.
Riders wait at a bus stop with ample seating, good lighting, and textured curb edges that improve accessibility for those with visual impairments.
Road Safety Infrastructure for Public Transport
Bus lanes are one excellent option for improving the safety of public transport. Not only do they improve travel times, but they also give buses a safe lane for stopping without interrupting car traffic. In a 2019 study by the Maryland Department of Transportation, bus lanes reduced bus-involved crashes by 12%.2
Raised medians can also help keep transit users safe from oncoming traffic as they get on and off a public transport vehicle.
Railway crossings are also an essential tool in making roads safer for public rail.
Safer Spaces for Public Transport Users
To make public transit access points safer for riders, these tactics can be helpful:
Placing bus stops consistently along routes to make them easier to find.
Placing useful crosswalks near transit stops to prevent unsafe crossings.
Using apps, mobile webpages, and other methods to reduce wait times and make schedules, route maps, and other important information accessible.3
Ensuring that bus stops, stations, and other transit hubs are well lit.
Ensuring transit hubs are accessible to people with disabilities, providing ample seating and spaces for wheelchairs, strollers, baby seats, groceries, and so on.
Establishing more frequent service to ensure that people don’t have to wait alone at stations or stops.4
Cyclist Safety
Cycling activity boomed during the pandemic, increasing 37% across the U.S. between 2019 and 2022. But many roads are still unsafe for cyclists and in need of safety interventions to ensure increased biking doesn’t result in increased road deaths for these cyclists.
For example, early in the pandemic, Walk Bike Nashville (WBN) heard resident concerns about increased rates of speeding. They analyzed traffic volume and speed, and discovered that motorists took advantage of empty streets to drive much faster. In June 2022, 22% of drivers were traveling 30 mph over the speed limit on one key roadway.
Additionally, while bike lanes can improve safety for cyclists by increasing their visibility and giving them dedicated space on the roadway, not all bike lanes are created equal. While an unprotected bike lane is usually better than no bike lane at all, some bike lanes can still leave cyclists in the path of opening car doors, swerving vehicles, or improperly parked cars that block the bike lane entirely.
Bike lanes that are protected from vehicle traffic or dooring by central hatching, raised medians, various types of barriers, or even street art can keep cyclists much safer than unprotected bike lanes.
A visualization from StreetLight InSight® of average speed on Armour Road in the 2021 study period shows how the bike lane curtailed speeding. There are very few instances of vehicles traveling above 40 mph (shown in green) when that proportion was much higher before, about one in every 20 trips.
Pedestrian Safety
Unlike bicycling, walking activity has plummeted since the pandemic. An analysis of pedestrian activity in the top 100 U.S. metros and 48 states (excluding Hawaii and Alaska) between 2019 and 2022 revealed declines in every region, ranging from 23 to 49 percent.
Even with these declines, pedestrian road deaths reached a 40-year high in 2022, according to the Governors Highway Safety Association.5
As noted above, safe vehicular speeds are a crucial component of pedestrian and cyclist safety. Speed reduction tactics like road diets (see section below), widening sidewalks, narrowing lanes, and reducing speed limits can have huge positive impacts on pedestrian safety.
Increasing the visibility of pedestrians, especially at intersections, can also dramatically impact pedestrian safety. Tactics like daylighting — where the sides of the road near an intersection are kept free of parked cars and other visual obstructions — ensure drivers can see pedestrians and vice versa, reducing the risk of pedestrians being hit as they cross the street.
Reducing crossing distance also helps keep pedestrians safe by reducing the amount of time spent crossing vehicle lanes. Pedestrian refuges and bulb-outs are common ways to accomplish this goal. Signalized crosswalks and synchronized signal timing are also key to intersection safety for pedestrians.
Vehicle Safety
Many of the tactics explored above also promote vehicle safety. Slower speeds, attentive driving, and smooth traffic flow help keep drivers out of accidents. Reduced speed limits, clear signage, daylighting, and optimized traffic signals are just a few of the tactics discussed above that can also improve these safety factors.
Some additional tactics like rumble strips, median barriers, and roadside design improvements at curves specifically target improved road safety for vehicles.
Rumble strips are milled or raised pavement elements placed along the edge of a travel lane that cause vibration when driven over, alerting drivers when they are veering outside the travel lane.
Median barriers help separate opposing directions of traffic along a roadway, and help avoid head-on collisions on two-way roads.
Horizontal curves account for 27% of all fatal crashes, according to the FHWA.6 Improved signage, clear zones, slope flattening, shoulder widening, and various types of barriers and guardrails can all help improve these dangerous roadway segments. Clear zones and wide shoulders give drivers a safe place to regain control of their vehicle, while barriers and guardrails help keep them from veering off the roadway or into oncoming traffic.
What Is the Safe System Approach to Transportation Safety?
The Safe System Approach is a holistic strategy aimed at reducing road deaths to zero. This approach was originally inspired by the Vision Zero movement, which began in Sweden and has since gained traction across the globe.7
The goal of the Safe System Approach is to make the entire transportation system safer — from roadway infrastructure to vehicle design, driver education, and emergency response — so that no one is killed or injured while using roadways. It recognizes that people make mistakes and vehicles malfunction. Thus, roadways need to be designed in a way that accommodates human and mechanical errors to help prevent crashes, injuries, and fatalities.8
Part of what makes the Safe System Approach effective is that it focuses on making proactive safety improvements. For example, city planners may discover an area that experiences recurring safety issues, and set out to fix those issues. Under a Safe System Approach that relies on proactive safety planning, officials would also be able to flag sites that share the same design as the one experiencing safety challenges. They can then flag these similar areas, making improvements to prevent safety issues before problems arise.9
StreetLight’s Safety Prioritize tool helps planners and operations managers diagnose safety concerns and identify the best countermeasures based on the most up-to-date mobility data.
Top Ways to Improve Transport Infrastructure Safety for All
Beyond the safety interventions explored above for each mode of travel, there are a few common safety tactics that can benefit all road users. In step with a Safe Systems Approach to road safety, these tactics often achieve holistic changes to how roadways are traversed, rather than addressing safety concerns piecemeal.
Building Complete Streets
The “Complete Streets” approach builds on Safe Systems by focusing on roadway infrastructure that equitably addresses the needs of all road users — not just vehicles. This includes bikers, drivers, public transit users, pedestrians, and even roadside diners.
Just as importantly, the Complete Streets approach also takes into account all ages and abilities. That means designing features for potentially disadvantaged groups like the elderly, people who use wheelchairs or walking aids, or people with hearing and vision impairments.
Thus, most Complete Streets policies include provisions to add bike and bus lanes to roadways so that municipalities can improve safety and access for these modes. For pedestrians, Complete Streets improvements may include curb extensions, audio traffic signals for the vision impaired, safer crosswalk designs, or daylighting.
Road Diets
Road diets are a proven safety solution that can often be implemented at very low cost. In many instances, the only expense is the cost of restriping a roadway.
Roads on a road diet take one or more lanes of general vehicle traffic and transform them into something else: bike or pedestrian lanes, bus lanes, or even central turn lanes that can be used by vehicles traveling in both directions. In some cases, municipalities may also use the space from removed vehicle lanes to install or widen existing medians, sidewalks, or shoulders.
Road diets often work to lower vehicle speeds for improved cyclist and pedestrian safety, or even to promote public transportation options like busing. This often comes with added advantages, like reducing greenhouse gas emissions while creating more walkable spaces—or spaces that are more accessible to underserved populations who rely on public transit.
Temporary road diets can also be created using jersey barriers, traffic cones, or portable pylons — a tactic many cities used during the COVID pandemic to calm traffic. In Waterloo, Ontario, for example, authorities put up black-and-orange construction barrels along 30 kilometers of roadway to convert space previously devoted to vehicles into temporary bike lanes. A study by StreetLight confirmed that the new bike lanes increased bike activity by 39% while reducing vehicle speeds by 12%.
Although proposed road diets often raise concerns that reducing lanes could lead to increased congestion and longer travel times, studies often show that travel times do not significantly increase after the implementation of a road diet.
For example, in 2019, Armour Road in North Kansas City, Missouri underwent a series of improvements, including the addition of a new protected bike lane and pedestrian refuges. A before-and-after study by StreetLight shows a significant reduction in dangerous vehicle speeds, double the biking activity, and a negligible increase in travel times (around five seconds on average) along the corridor.
A painted crosswalk along with temporary pylons and traffic cones help calm traffic and protect cyclists on Armour Road in North Kansas City, Missouri.
The Data Behind Safer Transportation Infrastructure
As we’ve explored, there are many ways to promote safer transportation infrastructure — and identifying the best safety interventions for a given intersection, roadway, or community requires a deep understanding of existing conditions and the potential impact of various approaches.
Transportation data like vehicle volumes, bike and pedestrian activity, turning movement counts, vehicle speeds, and more can help transportation professionals choose the right countermeasures, anticipate their impact, and measure before-and-after success.
Planners and engineers often rely on data from permanent traffic counters, manual counts, or surveys to understand existing conditions and anticipate impact — but not all roads have counters installed, and manual counts and surveys can suffer from sample size issues and bias.
Online transportation data analytics can help fill data gaps and avoid putting staff in harm’s way to collect reliable information on how people and vehicles move. The video below shows how DOTs, MPOs, and other agencies can leverage online analytics to perform safety studies and choose the right countermeasures for their region.
For a deeper dive into key safety metrics and how to use them to diagnose dangerous roadways, choose countermeasures, secure funding, and measure success, download our Practitioner’s Guide to Transportation Safety.
1. U.S. Department of Transportation, “The Roadway Safety Problem.” Feburary 2023
2. Maryland Department of Transportation. “Dedicated Bus Lanes Before and After Study.” February 2019
3. Rural Health Information Hub. “Models that Increase Access to Public Transportation.”
4. New York University Rudin Center for Transportation. “The Pink Tax on Mobility: Opportunities for Innovation.” February 2022
6. U.S. Department of Transportation Federal Highway Administration. “Roadside Design Improvements at Curves.”
7. U.S. Department of Transportation Federal Highway Administration. “Zero Deaths and Safe System.” August 2023
8. U.S. Department of Transportation Federal Highway Administration. “NHTSA’s Safe System Approach: Educating and Protecting All Road Users.” Winter 2022
9. U.S. Department of Transportation Federal Highway Administration. “The Safe System Approach: How States and Cities Are Saving Lives.” Winter 2022
Balancing Road Safety and Congestion in Oakland: Big Data Analysis Reveals Potential Solutions for a Dangerous Corridor
Balancing Road Safety and Congestion in Oakland: Big Data Analysis Reveals Potential Solutions for a Dangerous Corridor
Part of Oakland’s High Injury Network, Grand Avenue was slated for a safety overhaul, but a 2023 plan for the roadway prioritizes vehicular throughput over traffic calming measures. Big data analyses can help planners and advocates maintain traffic flow and make streets safer for walking and biking.
In 2021, traffic fatalities in the U.S. reached a 16-year high with nearly 43,000 people killed, a 10.5% increase from 2020. In my hometown of Oakland, the Department of Transportation Director called traffic fatalities an ‘epidemic’, citing 35 deaths in 2022 — the highest number of fatalities in the last 10 years.
To address this, Oakland, like many state and local governments across the country, set in motion an effort to reduce these tragedies in their 2023 Strategic Plan, citing the following safety strategies:
Adopt a Vision Zero policy and pledge to eliminate traffic injuries and deaths
Inform safe designs and infrastructure decisions with data and analysis
Incorporate safety and Complete Streets policies into road design processes
OakDOT’s Multimodal High Injury Network map highlights Grand Ave. among Oakland’s 6% of street miles that account for 63% of severe and fatal crashes.
Grand Avenue is among Oakland’s most treasured corridors. It serves as a major connector between Downtown and residential neighborhoods, hosts major commercial businesses and destinations, and border’s Lake Merritt, Oakland’s most prominent recreational park. But it’s also on Oakland’s High Injury Network, a group of roadways that represent only 6% of street miles but account for 63% of severe and fatal crashes.[1] As a traffic safety advocate and lifetime resident in the East Bay, I was excited to learn a plan was underway to redesign Grand Avenue with safety in mind.
But in June 2023, a new plan for Grand Avenue was published — one that prioritizes vehicle throughput at the potential expense of non-vehicle road users like cyclists and pedestrians.[2] Confused by this new direction, I wanted to use my experience as a Product Manager of Data & Metrics at StreetLight to see if the data could support safety improvements that would still assuage concerns over congestion on Grand Avenue.
Below, I’ll share what my analyses uncovered, and explore how DOTs can use multimodal data to navigate the difficult job of aligning stakeholders and negotiating competing priorities. But to contextualize these findings, it’s important to first dive a little deeper on the history of Grand Avenue.
2018 Grand Avenue Mobility Plan Prioritizes Safety and Traffic Flow
In 2018, Oakland’s Department of Transportation (OakDOT) published the Grand Avenue Mobility Plan, a comprehensive study that used a collection of data sources — including community engagement surveys and StreetLight’s Trip Speed, Roadway Volumes, and Origin-Destination Metrics — to take stock of the mobility, economic, and demographic conditions along Grand and present various redesign options.
The report states that the top two local goals are to “Serve existing residents’ transportation needs, and to improve the safety and comfort of those walking and biking along and across the corridor.” Taken together, these two goals speak to a nuanced and challenging balancing act that urban transportation professionals are constantly navigating: Should a corridor’s design prioritize the movement of vehicles or the safety and comfort of those not in vehicles?
These two goals can often seem at odds, but they don’t have to be.
While infrastructure and operations that benefit walkers and bikers — like bike lanes and reduced speed limits — can raise concerns over congestion and traffic delays, a deeper understanding of existing conditions can often reveal road design options that benefit both drivers and those outside vehicles.
But planners and engineers need robust, multimodal data to weigh all the options.
Existing Conditions on Grand Avenue: Broadway to Grand Lake Theatre
Of the corridor’s four sections, the stretch that connects Uptown to the Grand Lake Theater, which defines the northern border of the lake and park, is the first that will undergo a redesign. This section serves restaurants, businesses, visitors to the park, and the residents of the Adams Point neighborhood. It also connects downtown Oakland to the Hills neighborhoods and highway 580.
As of June 2023, the plan is at the 35% stage, and construction could begin as soon as 2024. [3]
A cross-section of Grand Avenue shows existing infrastructure on the corridor segment between Harrison and MacArthur. Image Source: OakDOT’s Grand Avenue Mobility Plan.
Existing conditions along the corridor feature two multi-use travel lanes, a center turn lane, as well as unprotected bike lanes and parking on each side. There are signalized crossings, but they are spaced far away and do not feature pedestrian islands at the median. Meanwhile, there are also very few curb bulb-outs, which function to improve safety by reducing crossing distance.
Importantly, the existing two travel lanes allow cars to travel quickly and unpredictably, making conditions unsafe for bicyclists and pedestrians. In San Francisco, a 2023 study from SFMTA showed that while 4+ lane roads were only 14% of the network, they constitute 53% of the collisions with bicyclists.[4]
The 2018 Grand Avenue Mobility Plan proposes multiple redesign alternatives, most of which include traffic calming measures that would reduce the number of vehicle lanes and repurpose roadway space for non-car travel such as bus and bike lanes or protected pedestrian medians. This type of roadway treatment is commonly referred to as a road diet — a traffic calming tactic that is proven to improve road safety, though it often prompts concerns over traffic congestion.
Corridor cross sections show four alternatives for a Grand Avenue redesign, which could include lane restriping and roadway construction to make room for medians, protected bike lanes, or dedicated bus and bike lanes.
Given the documented dangers of 4-lane roads and scarcity of existing infrastructure on Grand protecting pedestrians and cyclists, it makes sense that in the 2018 Plan, the most popular option was the Bicycle/Micromobility focus.
However, while earlier design stages maintained this emphasis on calming traffic and improving bike and pedestrian safety, the 35% designs published June 2023 focused on Vehicular Throughput instead.
There are many competing pressures that may have caused this reversal, but the most likely driver of a decision like this is the concern that vehicle volumes are too high for a single lane, resulting in poor Level of Service and congested traffic.
When considering changes to the road design, each corridor needs to be analyzed carefully to balance the needs of motorists, pedestrians, bicycles, transit, and other roadway users. This is where having access to better data can help practitioners pinpoint problem areas and determine how to create a design that avoids gridlock, but also promotes safety.
See which U.S. regions are recovering from a nationwide decline in walking
Analyzing Grand Avenue’s Current Traffic Conditions With Big Data
Generally, the safety on an urban collector like Grand boils down to pedestrian exposure to vehicles moving at high speeds. In the following analysis, I use StreetLight to examine conditions on Grand with the purpose of illustrating whether a road diet treatment — including reducing the lanes and speeds of vehicles — is appropriate, and how it would impact both pedestrian safety and congestion.
To do so, we must answer these fundamental questions:
Where is pedestrian activity highest?
Are vehicle speeds unsafe and where are vehicle speeds highest?
Do vehicular volumes warrant having two lanes in each direction?
Pedestrian Exposure on Grand
My first step was to identify where the most pedestrians are exposed to high-speed vehicles. To do this, I analyzed pedestrian activity at each intersection and overlayed vehicle speeding patterns. Measuring relative pedestrian activity can help transportation planners know where safety-focused interventions can have the highest impact.
A StreetLight InSight® analysis shows pedestrian traffic volumes on the Adams Point segment of Grand Ave.
In the map above, you can see that the highest pedestrian activity closely aligns with the section of Grand that borders the park. The other outlier is on the east corner of the lake, which is the intersection with the largest distance between crossing features such as curb extensions, center medians, or crosswalks (shown below).
Figure 17 of OakDOT’s Grand Avenue Mobility Plan shows existing infrastructure along the Adams Point segment, including pedestrian safety features like crosswalks and curb extensions.
The second step is to analyze vehicle speeds on the corridor, to determine where and when vehicle speeds are dangerous. StreetLight can be used to analyze the 85th and 95th percentile speeds, the standard method for measuring speeding vehicles.
For this analysis, I’ve zeroed in on weekdays from 8-9am, when families are walking to school and people are commuting, as well as weekend days from 12-1 pm, when people are visiting the park.
A StreetLight InSight® analysis shows average travel speeds along the Adams Point segment of Grand Ave. Higher speeds appear in red.StreetLight data visualized in QGIS shows where pedestrians face the most danger from speeding vehicles along Grand Ave.
Looking at the 95th percentile, the data shows that vehicles are often speeding in excess of 10 MPH above the speed limit during critical hours. Importantly, by overlaying the speed and pedestrian activity, it’s clear that the same areas with the most pedestrian activity also exhibit dangerous speeds.
Exposure analysis like this reveals precisely where the highest value interventions could be made. Pedestrian median islands, bulb outs, and high-visibility crosswalks are among the tools planners use to improve safety with or without reducing lanes.
Beyond these pedestrian safety features, the most effective way to reduce fatalities is to reduce speed, which is where concerns about congestion often surface. That’s because vehicle speeds and roadway capacity are interconnected — a phenomenon that was highlighted during the COVID pandemic, when a drop in vehicle volumes increased the rate of speeding.
To put it simply, when there is excess capacity, drivers will tend to use the extra space to move more quickly. Conversely, when there is less room for vehicles, drivers will tend to slow down.
This is where a deeper dive into vehicle travel patterns on Grand Avenue and adjacent roadways can help evaluate the corridor for lane reduction.
Vehicle Capacity on Grand
When considering how many lanes a corridor should have, traffic engineers will typically look at each direction separately and use the maximum hourly volume to determine the appropriate treatment that avoids congestion. The Federal Highway Administration Road Diet Informational Guide suggests that urban arterial lanes can likely support 750 Vehicles Per Hour (VPH), and possibly up to 875 VPH, but it depends on signal spacing, presence of turning lanes, and other factors.[5]
A StreetLight InSight® analysis shows vehicle volumes along the Adams Point segment of Grand Ave. Higher volumes appear in red.
To study optimal road capacity, first we need to look at how volumes change across the corridor. The image above shows that the corridor can reasonably be divided into two segments with distinct volumes, one along the lakefront, and one from the lake towards downtown. The hourly trends (seen at the bottom of the image) show that traffic peaks on weekdays between 5 and 6 p.m.
Next, the chart below shows how hourly volumes fluctuate during the weekday and weekend day, for each direction.
Data from StreetLight shows hourly directional traffic volumes fall below maximum suggested volumes for a single lane corridor, except during peak weekday evening hours.
The data shows that while most of the day falls below 875 VPH, weekday evening commute hours reach above the threshold recommended for 1-lane corridors. Therefore, according to traditional approaches to capacity planning, with no other changes to expected driving behavior, reducing the travel to one lane would likely cause congestion during those hours.
However, what the capacity benchmark fails to take into account is how traffic would organically reroute to underutilized roadways. Here, Streetlight can be used to understand through traffic behavior, as well as understand nearby capacity and whether it’s likely to help offset capacity changes on Grand.
Data from StreetLight reveals that 25% of Grand Avenue traffic, on average, is cut-through traffic bound for Highway 580.
The charts above show where people on Grand are coming from and headed to. On average, around 25% of vehicles are using Grand to get to Highway 580. During the peak hour, when congestion would occur, that number jumps to 30%. Furthermore, looking at where traffic is coming from, it’s noteworthy that 20% of peak hour traffic on Grand originates as far west as Martin Luther King Jr. Blvd.
During peak hours, 20% of Grand Avenue traffic originates from Martin Luther King Jr. Blvd., according to a StreetLight analysis.
While current conditions indicate that reducing the number of lanes risks congestion during peak hours, there is also evidence that much of this traffic is headed to the freeway and would end up naturally re-routing away from Grand Avenue. Further analysis should be done on the roadways where this traffic is expected to be diverted to determine if they have the capacity to take on the additional traffic.It should be noted that beyond keeping the current number of lanes, there are other ways to manage congestion, like retiming traffic signals or implementing a parking-convertible traffic lane during the heavily trafficked evening commute hour. Finally, and importantly, congestion can be reduced by promoting modeshift to transit and active transportation.
Based on my analysis, there is reason to suspect that a road diet on Grand Ave. could still be a viable solution to safety concerns along this high-injury roadway, and may merit particular consideration on the areas of the roadway where high pedestrian activity and high speeds dangerously coincide.
Although traffic flow and pedestrian safety on Grand may appear to be in conflict, access to robust mobility data for this and adjacent corridors helps reveal road design alternatives that accommodate both.
Vehicle metrics shown here were collected from January to April 2023. Pedestrian activity was collected from November-April 2022.
Explore the resources listed above and don’t hesitate to reach out if you have any questions. We’re committed to fostering a collaborative community of transportation professionals dedicated to building a better future for our cities and communities.
When we founded StreetLight Data back in 2011, our sole focus was to help educate and plan for electric vehicles (EVs). We quickly realized that our transportation data would have a more significant positive impact if we expanded our mission beyond EV data analytics. However, EVs are still one of my deep interests: I drove a Chevy Volt for several years before going car-free, 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 and promote sustainable transportation networks, 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 U.S. and abroad — and the funding now available for EV charging infrastructure through Bipartisan Infrastructure Law (BIL) programs like the National Electric Vehicle Infrastructure (NEVI) and Charging and Fueling Infrastructure (CFI) grants — now seems like the right time to explain how Big Data can help.
As transportation infrastructure planners, it’s important to recognize that most charging will be done at home. But convenient, cost-effective out-of-home charging is necessary to get the adoption levels we want from EVs. EV charging analytics derived from Big Data can support better out-of-home electric vehicle charging in four ways:
Site Selection – Macro: Scan an entire city to find the best places for EV charging.
Site Selection – Micro: Analyze and validate individual potential sites.
Education and Awareness: Select highly visible “activity centers” for chargers to maximize public exposure.
Right Sizing: Improve estimation of grid load and electrical cost (and ancillary grid service applications).
In this blog post, I will discuss each of these topics using EV charging analyses created in StreetLight InSight®. (That’s our online platform for transforming location records created by connected devices into travel pattern analytics.)
Site Selection – Macro: Scan an Entire City to Find the Best Places for EV Charging
Although most EV charging will be done at home, the well-documented phenomenon of “range anxiety” is slowing adoption. Using transportation analytics, we can scan an entire city or region to find the best places for EV chargers. On-demand EV data analytics allow us to define “best” in different ways, and easily run multiple scans at very low marginal cost and effort.
Here’s a quick video on how this works in the StreetLight InSight® platform:
For example, let’s say that I believe the best charging station locations will be the workplaces of people who:
Drive more than 40 miles a day (so they might want to recharge mid-day),
Live in neighborhoods that currently have high hybrid adoption, and
Go to the same workplace almost every weekday.
I can scan every block or property in a region to highlight where such early adopters tend to park. In Figure 1 below, you can see this scan on a 1-kilometer grid in the San Francisco Bay Area. However, I could also use StreetLight InSight® to scan for other key characteristics, for example:
Where people from a particular income bracket go when they’re not working or at home,
Where cars tend to be on longer drives when they still have 100 miles to go,
Where people who don’t have driveways tend to park.
Figure 1: A scan of the San Francisco Bay Area that highlights the work neighborhoods of people who drive more than 40 miles per day and currently live in high-hybrid adoption areas.
Identify the best EV charging locations with electric vehicle data
Site Selection – Micro: Analyze and Validate Individual Potential Sites
Sometimes, the question of EV charger location optimization is more constrained. Perhaps a retail brand has 200 locations, and wants to deploy EV chargers to 20 of them. Which 20 locations are the best? Using similar logic as described above, individual locations can be scored for certain characteristics of drivers at or near the location (see Figure 2 below).
Figure 2: A chart showing EV “scores” based on three criteria for a group of stores from the same brand.
This micro-site selection analysis can also be used to select amongst individual properties and locations within a single neighborhood that a macro-scan previously identified as a strong candidate (see Figure 3 below).
Figure 3: The highest scoring EV parcels within 500 meters of an off-ramp in Texas that a macro-scan previously identified as “high EV convenient.” Parcels shaded in red have the best scores for EV convenience.
Earn customer visits with EV charging data for your business locations
Simply being seen is one of the more important features of EV chargers. Chargers remind citizens of the availability of EVs, and they build confidence that charging will be easy and convenient. Analyzing for visibility can be a simple numbers game. We want to find out:
Which roadside areas are seen by the most people driving by?
Which parking lots are parked in most often?
Transportation analytics can help answer both of these questions. In Figure 4, Retail Group C’s parking lot has more parking events than A or B. From a visibility perspective, it may be the best bet, though not necessarily from a charging load perspective.
Right Sizing and Better Estimation of Grid Load
The distribution of the time of day during which charging occurs can make a big difference in terms of the number of chargers needed (and thus the installation cost), the load on the grid, and the costs associated with charging. Depending on the locality, EV charging rates can vary by time of day. For businesses and commercial properties that face costs based on demand, charging can also trigger extra fees from their utility company.
Thus, knowing the time of day when EVs are likely to be charging is critical for estimating installation and operating costs. In addition, time of day information is necessary for anyone exploring more integrated vehicle-to-grid ideas. Figure 4 shows a parking load curve for three similarly-sized commercial parking lots in Texas that are located within one-half mile of each other along the same road. These are their key characteristics:
Lot A contains a movie theater and restaurants,
Lot B contains one very large big box retailer, and
Lot C contains a group of four big box retailers.
Figure 4: This graph shows the parking load for three different commercial lots in Texas during a 24-hour period.
While Lot C has the most visitors per day, they peak during the midday and afternoon time periods. In many localities, especially those with hot climates, utility companies charge the highest rates during midday and afternoon. While Lot A has fewer total people, it peaks in the evening. At the same time, such a peaky load may mean that a lot of people want to charge at once, making it necessary to install a few more stations.
Depending on local rate structure and demand charging schemes, the cost of installing chargers at these three parking lots can vary widely, even though they are located close to one another and have similar profiles. Using “generic” load curves won’t reveal this variation – only working with comprehensive and flexible EV charging analytics can.
For more information on StreetLight’s electric vehicle data analytics for charger site selection, emissions measurement, and more, check out our EV charging data solutions.
Identify the best EV charging locations with electric vehicle data
Explore the resources listed above and don’t hesitate to reach out if you have any questions. We’re committed to fostering a collaborative community of transportation professionals dedicated to building a better future for our cities and communities.
What Are Complete Streets and How Can Analytics Help Us Build Them?
What Are Complete Streets and How Can Analytics Help Us Build Them?
Focusing on car-centric infrastructure can compromise roadway safety, increase emissions, and leave many without a reliable way to get from A to B. But Complete Streets policies promote safe and equitable outcomes for all road users.
We have a tendency, particularly in the U.S., to design roads for cars and trucks. Decades of vehicle-centric city planning have exacerbated this tendency, as sprawling metropolises make travel by car essential for most Americans.
This focus on car-based travel leaves many people behind. Pedestrians and cyclists face unsafe roadways without bike lanes, sidewalks, or crossings. Those who cannot drive or afford a car struggle to get to work via transit or access essential resources like grocery stores and doctors. People living near congested highways — predominantly communities of color [1] — suffer the effects of both noise and air pollution, impacting health outcomes.
In the face of these realities, we need a paradigm shift in how we design streets. Instead of vehicle-first transportation systems, we need people-first transportation systems. And this new paradigm is already gaining ground through programs like Complete Streets.
What are Complete Streets?
“Complete Streets” is an approach to roadway policy and design that focuses on enabling safe mobility for all road users — drivers, pedestrians, bikers, and public transit riders alike, across the full spectrum of ages and abilities. [2]
For example, a Complete Streets policy may call for the implementation of pedestrian traffic signals that are accessible to those with visual impairments. Policies may also call for added bike lanes and bus lanes to improve safety and access to these transportation modes, or the implementation of curb extensions, crosswalks, and daylighting to provide safer paths for pedestrians.
Many public officials at the local, regional, state, and federal levels are working to build better bicycle, pedestrian, and transit infrastructure through Complete Streets policies. The concept of Complete Streets is now mainstream in transportation, with planners striving to design and build streets that safely accommodate all transportation modes and users. In fact, according to the National Complete Streets Coalition, over 1,700 Complete Streets policies have been passed in the U.S., including those adopted by 37 states, Puerto Rico, and Washington D.C.
In this article, we’ll discuss several benefits to Complete Streets and how we can leverage transportation analytics to build more of them.
Why are Complete Streets more equitable?
Streets with multimode infrastructure offer more ways to travel, increasing mobility for everyone. Whether they drive, bike, walk, or use public transit, Complete Streets give them ways to get from point A to point B. This is especially crucial when point B is an essential resource like food, healthcare, work, or school.
Vulnerable populations, including people of color, people with disabilities, and those who are impoverished or experiencing homelessness are less likely to own or drive a car. Ensuring that non-car travel options exist increases access to mobility for these groups while also benefiting other travelers.
It’s important to note that the existence of non-car travel options doesn’t always ensure the accessibility of these options. Here, we mean accessibility in multiple senses — accessible for people with disabilities and accessible more broadly for all road users. Even when non-car mode options exist, there can be barriers to their use such as inadequate seating at bus stops or English-only signage.
In the video below, Alex Bell of Renaissance Planning explains how he used multimode analytics from StreetLight to compare mode availability to mode utilization in order to diagnose barriers to access for vulnerable populations.
Access to non-car transportation options can also help ensure fewer people suffer from homelessness. According to Jacob Wasserman, a researcher at UCLA who conducted a meta-analysis on transportation and homelessness,
“Homelessness is first and foremost a housing problem, but transportation is so intimately tied into housing. People can only live in places they can afford, which is sometimes really far from [the things they need to reach] because of our transportation decisions.” [3]
And because Complete Streets allow more opportunities for non-car travel, they also reduce overall Vehicle Miles Traveled (VMT), leading to improved air quality and less noise pollution for people living near highways, a group made up disproportionately of communities of color. That brings us to the next question….
Why are Complete Streets more climate-friendly?
Transportation is the top source of greenhouse gas (GHG) emissions in the U.S., at 27% in 2020, according to the EPA. That means the transportation industry has a critical role to play in addressing climate change.
Because Complete Streets reduce our reliance on single-occupancy vehicle (SOV) trips by making it easier to use shared mobility and active transportation options, they also lower total Vehicle Miles Traveled (VMT). By reducing the number of cars on the road, Complete Streets also help reduce traffic congestion, which means less time stuck in traffic with the engine running. With fewer miles traveled and less time spent in cars, emissions drop and air quality improves.
Adding Complete Streets infrastructure to existing roads can also have the effect of calming traffic. For example, road diets — which reduce the number of vehicle lanes and often repurpose the space for multimodal infrastructure — tend to reduce vehicle travel speeds and vehicle throughput without causing the congestion that would lead to increased emissions. Since vehicles are less fuel efficient and emit more CO2 per mile traveled at higher speeds, this means multimodal Complete Streets infrastructure can sometimes double as traffic calming measures that reduce emissions while also improving safety.
In the example below, AEC firm ATCS identified opportunities to invest in multimodal infrastructure on Route 234 Business in Prince William County, Virginia with the goals of reducing congestion, increasing safety, and making travel more sustainable.
Creating these opportunities for mode shift is crucial to decarbonizing our transportation networks, although they are just one strategy we can use to reduce overall emissions. We explore additional strategies in our free guidebook, Measure & Mitigate: Transportation Climate Data Solutions.
Why are Complete Streets safer?
As roads emptied and travel speeds increased during COVID, severe crashes spiked. This made many cities less safe for bikers and pedestrians in particular, highlighting the urgency of infrastructure improvements and traffic calming measures to make streets safer.
Smart Growth America’s map of most deadly vs. least deadly metro areas for pedestrians.
When streets lack multimodal infrastructure like signalized crossings and bike lanes, that doesn’t prevent non-car road users from needing to travel. Many still need to walk, bike, or use public transportation in order to access basic necessities, forcing them to brave streets that lack the infrastructure needed to keep them safe as they travel.
Adding accessible sidewalks, crossings, bike lanes, bus lanes, signage, and other Complete Streets infrastructure helps ensure that not only can people travel, but they can do so safely.
Complete Streets improvements may also mean making streets safer not just for travelers, but also for road workers, outdoor patio diners, and homeless people sheltering under overpasses or asking for help at intersections. In the example below, the City of Pasadena implemented various traffic signal timing techniques to reduce the speed on corridors with outdoor dining, as well as other arterials.
For more strategies to make streets safer, download our free Safety Handbook.
How can we build more Complete Streets?
With all these benefits to Complete Streets, how can transportation professionals make headway on ensuring more of our streets serve all road users?
Implementing official Complete Streets policies can provide the incentive and accountability to get started. In the U.S., the Federal Highway Administration (FHWA) offers guidance for transportation agencies looking to establish Complete Streets policies. [4]
The Federal Transit Administration has also waived the local funding match requirement for Complete Streets planning activities to receive funding through the federal State Planning and Research Program (SPRP) and Metropolitan Planning Program (MPP) through the end of 2026.
Because so many factors might go into making streets “complete,” — bike lanes, bus stops, signage, sidewalks, well-timed traffic signals, and so much more — understanding existing roadway conditions, mode usage, traveler demographics, and the impact of past projects are key. This is where digital transportation analytics come in to help agencies identify high-priority improvements and develop data-supported implementation plans.
StreetLight InSight® allows users to compare bike activity to trip speed info to pinpoint where bikers may face dangerous road conditions.
Transportation analytics for Complete Streets
The right data is necessary to identify and prioritize high-impact roadway improvements, secure project funding, and earn public and political buy-in for your proposed solutions. While traditional data collection methods like sensors and surveys offer helpful data points to support these goals, they often present limitations in scope and sample size. Digital, on-demand transportation analytics fill in the gaps to enrich our understanding of travel patterns and the needs of road users.
Because installing new multimodal infrastructure can be costly and time-consuming, one of the easiest ways to make streets more complete is to evaluate the performance of existing infrastructure and identify opportunities for optimization.
Say you wanted to optimize bus schedules or add stops to an existing route to adapt to shifting travel demand. An Origin-Destination (O-D) analysis using digital traffic data can illuminate where lots of people are traveling between work and home, while the ability to view traffic volumes by time of day can help determine when most people need to travel. Aggregated demographic data can also be overlaid onto travel patterns to understand where vulnerable populations would most benefit from added stops.
For example, when commuting patterns shifted after COVID, bus ridership in San Francisco dropped disproportionately to other modes. On-demand transit metrics helped SamTrans understand shifting travel behaviors and boost bus ridership by 30% after adjusting bus schedules.
When installing new infrastructure such as a bike lane or pedestrian bridge, digital analytics help agencies prioritize high-impact locations to invest in multimode infrastructure. For example, one Parks & Rec group used O-D analysis to determine the daily number of bikeable trips (five miles or shorter) to a target destination, justifying their investment in a new trail and bridge facility.
Similarly ATCS used digital transportation analytics to develop a multimodal scoring system for DC DOT that would help them pinpoint infrastructure gaps and determine where new projects were most needed:
Want to learn more about how digital transportation analytics can power effective Complete Streets initiatives? See how on-demand traffic data supports:
Yoo Min Park and Mei-Po Kwan, “Understanding Racial Disparities in Exposure to Traffic-Related Air Pollution: Considering the Spatiotemporal Dynamics of Population Distribution.” Int J Inviron Res Public Health 17 (Feb 2020): 908.
U.S. DOT, “Complete Streets,” August 2015.
Kea Wilson, Streetsblog USA. “Three Ways DOTs Can Help the Unhoused – On and Off the Road.” February 23, 2023.
Federal Highway Administration (FHWA), “Make Complete Streets the Default Approach.” February 2023.
Make streets safer with data-informed infrastructure planning
Explore the resources listed above and don’t hesitate to reach out if you have any questions. We’re committed to fostering a collaborative community of transportation professionals dedicated to building a better future for our cities and communities.
Corridor Studies Explained: What they are and how analytics make them quicker and cheaper
Corridor Studies Explained: What they are and how analytics make them quicker and cheaper
Corridor studies create crucial insights that keep people and goods moving safely, but they also demand ample resources from agencies already grappling with budget and staff limitations. On-demand analytics streamline data collection, offering a quicker and less costly path to the insights that inform corridor improvements.
When it comes to mobility, not all roads are created equal. That’s why transportation professionals devote considerable time and resources to major corridors — like interstates, state routes, and other major thoroughfares — to ensure people and goods can get where they need to go safely and efficiently.
To understand how mobility can be improved or maintained along these major arteries of travel, corridor studies are essential. They enable transportation professionals to understand existing conditions, project future conditions, prioritize improvement projects, earn stakeholder and public buy-in for these projects, and ensure environmentally-friendly transportation systems.
These outcomes are so important that corridor studies are often required under federal and state regulations before transportation projects can be approved or funded. But these studies are also demanding, unwieldy, and time-consuming for those who carry them out. They typically take several months or even years to complete, which can deplete already-thin agency budgets and frustrate constituents who want to see action.
So what is a corridor study exactly, why are these studies so important, how are they conducted, and how can technological innovations help shorten timelines, lower costs, earn stakeholder buy-in on projects, and deliver a fuller picture of corridor connectivity? We explore all these questions below.
What is a corridor study?
A corridor study is a planning project that aims to characterize existing and future roadway conditions along a major connective roadway (i.e., corridors) used by vehicles, bicycles, transit, and pedestrians. The scope of a corridor study may be hyper-local (a few miles or less) or it may account for dozens of miles of roadway, as is often the case when studying a major interstate.
Interstates and other major connective highways are the most common subjects of corridor studies.
Corridor studies are often multi-purpose projects that support a wide range of transportation goals such as:
Improving Operations
Economic Growth & Stability
Sustainability & Resilience
Safety & Equity
Communication & Public Relations
Meeting Regulatory Requirements
Estimating roadway capacity
Accommodating freight movement
Ensuring resilience against climate change, natural disasters, and general deterioration
Revealing safety concerns and potential improvements
Gaining community buy-in for proposed projects
Satisfying regulatory requirements for a project that is already planned for a funding cycle
Quantifying and minimizing the environmental impact of travel
Addressing inequitable infrastructure
Minimizing impacts to the traveling public during implementation
Estimating costs of maintaining or improving a corridor
Developing a travel demand model to help forecast future travel conditions
Expanding multimodal access and designing Complete Streets
Assisting other transportation agencies like MPOs and RPOs in identifying future projects along a corridor
The outcome of a corridor study is typically a corridor plan, which lays out recommendations for infrastructure projects and operational changes that address concerns revealed by the study. Along with these recommendations, a corridor plan usually includes estimated costs for the proposed measures as well as potential sources of funding to cover those costs.
To encourage a transparent planning process with buy-in from the public and other stakeholders, study findings and recommended projects are typically shared with partners, regional governments, advocacy groups, and the public through a published report.
Long-Range Corridor Plans
This type of corridor plan typically studies a major interstate or other highway and aims to establish justification for upcoming improvements, which may be implemented at a much later date (sometimes 10 or more years after the plan is created). In many cases, the plan is designed to address requests tied to political interests.
Long-range corridor plans are often conducted on a recurring basis (e.g., every 10 years or so) to keep up with shifting travel demand and offer guidance to DOTs, MPOs, RPOs, and other stakeholders who may design or carry out corridor improvements recommended by the plan.
NEPA Corridor Plans
The National Environmental Policy Act (NEPA) requires federal transportation agencies to report on the environmental impact of proposed projects, such as the construction of highways and other publicly-owned facilities. These reports must include an exploration of alternatives to demonstrate why the project proposed is the best available option.
NEPA corridor plans help avoid unforeseen environmental consequences of corridor projects, such as increased risk of erosion.
A NEPA corridor plan is usually established once a project and set of projects along a corridor has been planned for a funding cycle (to be funded within 10 years). As part of the planning process, public review must be sought out and incorporated in order to satisfy NEPA requirements so that funding can move forward and projects can be implemented.
Sometimes projects are put on hold and the NEPA process languishes. In this case, when it is restarted, NEPA needs to be revisited along with any updates to existing conditions and forecasts. This is particularly true when a large funding stream becomes available.
Metropolitan Corridor Plans
MPOs regularly plan for network and corridor improvements in their region as part of their Metropolitan Transportation Plan (MTP). These corridor plans are often ongoing and evaluate many iterations of projects and project portfolios in their MTP.
If a project is not indicated with dedicated funding in a MTP, then it can’t receive federal dollars. MTPs are made for rolling 20-year periods and updated every five years.
While MTPs are typically managed and developed internally by large MPOs, AEC firms may be contracted to assist with planning and coordinating public involvement. AEC firms or research institutes may also assist in modeling and data collection. Project funding and later activities are typically provided by the state.
City/County Corridor Plans
A city DOT or Planning Department will also initiate more localized corridor planning activities. These may be done in coordination with the MTP, federal, and state funding processes or as part of local funding efforts. As with other types of corridor plans, AEC firms are often called upon to help with the planning process and public outreach.
These projects often support goals related to Complete Streets, access management, economic growth, safety, traffic signals, and local transit.
Streamline corridor analysis with on-demand metrics like VMT, VHD, Trip Speed, and more
In order to evaluate existing conditions and forecast travel demand on a corridor, a wide range of data must be collected. Traffic volumes for all vehicles, as well as bicycles and pedestrians, are just the beginning. Turning Movement Counts (TMC) at intersections, Origin-Destination (O-D) patterns showing how travelers use the corridor to get from point A to point B, and congestion metrics may also be collected. Additionally, analysis will typically include estimating LOS, VHD, VMT, Crash Rates, and Reliability Indexes.
Traditional data collection methods for corridor studies include:
Field observations
Staff are sent out to multiple locations along the corridor to collect roadway inventory and measure geometries
Roadway sensors
Sensors collect traffic counts, speeds, and turning movements
Crash reports
Existing crash report data is reviewed and used to derive crash rates and flag safety issues
Data from previous transportation studies
Past studies of the corridor are reviewed for additional insights and can help demonstrate change over time
Physical roadway sensors may be installed on roads to help measure traffic.
Because of the time and cost that goes into many of these traditional methods, transportation analytics are often used to supplement and streamline these measurements. Given the difficulty of collecting data across a large area — such as traffic counts for a whole interstate — not only do analytics save time and money, but they also allow transportation professionals to get a consistent snapshot of a corridor at the same point in time and from different perspectives. Multiple analyses can be run in minutes, and data can easily be segmented by factors like time of day or day of week.
Despite these advantages, analytics typically do not replace traditional methods entirely. For example, in order to assess conditions such as roadway geometry, guiderail erosion, and sight distance, manual field observations are often necessary. However, software-based analytics are often indispensable in deriving data like Vehicle Miles Traveled (VMT), TMC, VHD, and O-D patterns for a corridor.
Input from stakeholders and the public is also gathered during the study. This helps identify community priorities, provide insight into who the corridor serves, and inform viable projects. Since getting the public on board with upcoming projects is a key concern for corridor planners, these insights are crucial for developing data-backed recommendations that justify proposed plans.
The data that is collected may also be used to build travel demand models that help forecast future conditions along the corridor.
How analytics are making corridor studies easier and more complete
Because corridor studies combine so many elements and may inform decades of infrastructure projects, they often take months to years to complete, demanding considerable cost and effort along the way.
While total study costs vary dramatically based on the size of the corridor, hundreds of thousands of dollars are typically devoted to the process. For example, a 2020 corridor study by VDOT studying under three miles of roadway cost $100,000[1], while a study of just 4.7 miles of SR 303 in Bremerton, Washington, was budgeted at $500,000.[2] Corridor studies often cover much larger areas than these two examples, and thus costs escalate quickly.
Although certain data must be collected manually in the field, software-based transportation analytics can significantly streamline data collection, while providing a more holistic account of roadway conditions like traffic volume, congestion, O-D, and turning movements. Because historical data can be accessed on demand for any day of the week, time of day, or month of the year, these analytics offer a more complete view of roadway conditions than temporary sensors or manual field observations gathered over just a few days.
This Segment Analysis in StreetLight InSight® shows Vehicle Miles Traveled (VMT) along a corridor, segmented hourly with peak hours highlighted.
Additionally, on-demand analytics contribute to a more holistic understanding of roadway safety. Traditional safety analyses rely heavily on information from reported crashes, missing nuances from crashes which may not be reported and unsafe incidents which don’t result in crashes.This can provide an incomplete view of factors contributing to unsafe corridors and make it more challenging to pinpoint sections of roadway where safety improvements could make the biggest impact. But when corridor studies incorporate transportation analytics, factors like speed, bike and pedestrian activity, and turning movements by time of day or day of week can provide additional insight to inform safety solutions.
This sample analysis in StreetLight InSight® shows trip speeds along multiple road segments.
By incorporating Census data to overlay aggregated demographic info on other corridor data, on-demand analytics also assist planners and engineers in identifying existing inequities and proposing improvements that address these disparities so that corridors serve everyone. Traditional methods of data collection miss out on this equity lens, making it harder for transportation professionals to ensure equity-first infrastructure.
For example, a steering committee conducting a corridor study of PA Route 28 used StreetLight InSight® to analyze the geographic spread of the home locations of travelers, helping reveal who the corridor serves. The committee also leveraged StreetLight to understand trip purpose, O-D patterns, trip duration, and trip speed.[3] Another study of seven key corridors in Hartford, Connecticut, used StreetLight InSight® to collect travel patterns, including O-D and trip volumes by time of day.[4]
And analytics don’t just help with establishing existing conditions. Because of the additional nuance and granularity provided by on-demand analytics, this technology is also a boon for modelers looking to build complex travel demand models that help forecast future roadway conditions.
Additionally, analytics platforms can assist with NEPA plans by helping estimate emissions, reveal EV activity, and measure overall traffic on a corridor.
Finally, platforms like StreetLight InSight® assist planners in justifying proposed corridor projects to stakeholders and the public through data visualizations that put study findings into perspective.
So while analytics can’t replace the need for certain manual measurements and field observations, they can justify prioritization decisions for stakeholders and the public with validated data while saving time and money on data collection and modeling so transportation agencies can devote more time to designing and implementing safe, resilient, and well-operated corridors for all.
Virginia Department of Transportation, Shreve Road Corridor Study. December 2020.
Washington State Department of Transportation, SR 303 Corridor Study. May 2021.
Southwestern Pennsylvania Commission, Route 28 Corridor Study. November 2020.
Connecticut Department of Transportation, Greater Hartford Mobility Study Existing Conditions Report. December 20, 2021.
WEBINAR: See how on-demand analytics streamline corridor studies & clarify planning priorities
Explore the resources listed above and don’t hesitate to reach out if you have any questions. We’re committed to fostering a collaborative community of transportation professionals dedicated to building a better future for our cities and communities.
How Transportation Data Can Tell A Story Federal Grant Administrators Want To Hear
How Transportation Data Can Tell A Story Federal Grant Administrators Want To Hear
With $1.2 trillion at stake in the Bipartisan Infrastructure Law (BIL), cities and municipalities are developing applications for bridge improvements, rail expansion, safety upgrades, EV chargers, and much more.
To win federal approval, applicants need to tell a compelling story for why their project will improve the community across dimensions like congestion, environmental impact, equity, and safety. Telling that story isn’t as simple as putting numbers in bullets.
visualizations that can quickly and directly show impact
demographic data to understand who will benefit
Whether you want to build new bike lanes, revamp a truck route, or create an EV charging corridor, embedding these three elements in a grant application gives you a better shot at getting a grant administrator to yes.
StreetLight InSight® lets you visualize your results on the flyGrant applicants have used StreetLight for everything from highlighting commuting metrics to show a project’s economic value to using bike and pedestrian metrics to give the full mobility picture to origin-destination analysis to show regional benefit.
In Ohio, for example, the state DOT embarked on a project to revamp Interstates 70 and 71, which would improve corridors of the National Primary Highway Freight System and help reconnect communities adversely affected by redlining and the construction of those interstates.
To fund Phase 4 of the development, Ohio DOT applied for a federal Infrastructure for Rebuilding America (INFRA) grant and used StreetLight to make their case.
Using the platform, planners separated out passenger vehicles from commercial truck volume, proving the significant percentage of traffic on the corridor from freight movement. They used StreetLight’s visualization tools to show truck congestion in the existing corridor and make the case for how a new truck route would ease the national supply chain.
StreetLight InSight® Origins and Destinations for commercial trucks. 3D visualization with bar height depicting traffic volume of major origin and destination zones. StreetLight also allowed planners to establish baseline data that grant reviewers could validate to make sure the assumptions underlying the proposal were legitimate, and metrics available within the platform allowed the DOT to establish travel time savings from the revamp and project cost savings.
The proposal showed a clear positive impact on the national supply chain using easy-to-digest visuals and reliable metrics.
The result: federal authorities not only approved the grant but did not require any further petitioning.
For a step-by-step guide to winning transportation grants, download our e-book and take a deeper look at the tools and techniques that can get federal grant administrators to yes.
Drive Your Bid for Infrastructure Dollars
There are a limited number of dollars, and the stakes are high. Mobility metrics and demographic data can support your proposal for NEVI Program funds. StreetLight’s EV offerings will help you identify optimal charging sites along key corridors to serve your key priorities, grow EV adoption, and help shape our EV future as a nation.
The Deadline to Submit EV Plans (and Get NEVI Funding for Your State) Is Almost Here. Got the Mobility Data You Need?
The Deadline to Submit EV Plans (and Get NEVI Funding for Your State) Is Almost Here. Got the Mobility Data You Need?
Huge changes are about to occur in our electric vehicle infrastructure. More than 7.5 billion federal dollars are heading to the states, beginning with funds to expand our nationwide network of EV chargers ten-fold. With important funding deadlines coming up soon, states need to move fast. First order of business? State DOTs must closely examine the mobility landscape to identify and build a map of optimal EV charging locations in their regions.
Get Your AFC Nomination Reports and NEVI Deployment Plans Finished On Time
States will be apportioned infrastructure dollars through the newly-formed National Electric Vehicle Infrastructure (NEVI) Formula. To be considered for funds, states must designate Alternative Fuel Corridors (AFCs), highway segments with the current or planned infrastructure to support fully electric private and commercial vehicles. The NEVI formula also requires that AFCs take rural areas, air quality improvement, and access for disadvantaged communities into consideration.
Two important dates should be on your calendar.
May 13: Deadline for designating Alternative Fuel Corridors (AFCs)
August 1: Submission deadline for EV Infrastructure Deployment Plans to the Joint Office of Energy and Transportation
Mobility Analytics Help Answer Four Key Questions For Optimal EV Charging Site Evaluation
Even if your state has a solid EV charging network today, you’ll need to investigate whether your existing corridors are sufficient—and if they aren’t, identify where infrastructure gaps lie. Start with these four questions:
1) What is the existing traffic demand? Your first step is to identify the current traffic demand at various locations. You can use Metrics from the StreetLight platform to understand vehicle volumes (for all vehicles, not just EVs) at these locations and pinpoint trip activity hotspots. You can also evaluate highway exits in your state to determine which exits have the highest traffic demand. These insights will help you decide which exits will provide accessible and reliable charging locations for long-distance trips. Existing traffic demand data will greatly help you evaluate AFCs for your NEVI funding proposal.
2) What are the aggregate demographic characteristics of existing drivers at these sites? StreetLight InSight® combines traffic volume data with demographics such as education level and household income, analyzing where aggregate groups of people live, work, and shop. Beyond spotting activity hotspots, the data reveals the purpose behind drivers’ travel. This includes whether people are coming, say, from home to the shopping plaza or stopping there on the way home from work. These Metrics help determine the traveler profile at these potential or existing EV sites. This greatly aids in EV charger planning, because it shows the precise hotspots—like a mall or a theater, or an office park—where people purposely schedule activities to access public charging stations.
3) Where are vehicles coming from and going? Origin-Destination Metrics and Top Routes are important pieces of the infrastructure puzzle. StreetLight InSight® will show you how far travelers have come to reach a popular destination, as well as the most frequently used roads and highway corridors. These insights will help planners determine where to build key nodes of a larger charging network or corridor. They also determine the types of chargers that might best serve travelers.
These Metrics are a great place to start when trying to determine where the traffic demand is along AFCs within a region.
4) How long are vehicles staying at certain sites? To build a viable charging infrastructure, you must understand dwell times at destinations like shopping plazas, office buildings, movie theaters, and more. Once you know how far people travel to get to primary destinations, you’ll need to see how long they stick around. This information will help you predict charger use and the type of chargers that will best support travelers. For example, 30-minute DC fast chargers are needed outside of a grocery store or a movie theater. They’re pricey but absolutely necessary. On the other hand, Level 2 chargers—which are slower but less costly—would work well at longer dwell destinations like a hotels.
Two Interstate Exits Have Very Different Charger Needs
At two different Massachusetts Turnpike exits, the dwell time (the length of stay at a given location) varies tremendously. Exit 9, filled with shops, grocery stores, and restaurants, shows that vehicles are mostly parked for 20-60 minutes—enough time to grab a burger. Exit 12, with its hotels, offices, and entertainment park, generally keeps people lingering for more than four hours. Big difference.
Comparing dwell time of different exits on a highway corridor
These dwell time findings offer a great view into the type of chargers that would make sense for each exit. Investment in DC fast charging would be more appropriate for Exit 9, whereas Exit 12—which draws the longer stays—would be very well served by less expensive Level 2 or 3 chargers.
Looking to Attain Specific Policy Goals (Like Equity)?
StreetLight Data offers a regional scanning tool to identify specific charging gaps and provide insights into aspects such as utilization potential, trucking, and identifying prime locations. If you’ve already located key sites, but need data to support equity initiatives—like Justice40—layer on metrics to optimize for equity scenarios involving disadvantaged and low-income communities, as well as exposure to air pollution. Equity is a huge part of the future of EV infrastructure, so the sooner you gather the equity picture for your state, the better.
Drive Your Bid for Infrastructure Dollars
There are a limited number of dollars, and the stakes are high. Mobility metrics and demographic data can support your proposal for NEVI Program funds. StreetLight’s EV offerings will help you identify optimal charging sites along key corridors to serve your key priorities, grow EV adoption, and help shape our EV future as a nation.
Is Your Investment in Tourism Paying Off? Analyze the Impact.
Is Your Investment in Tourism Paying Off? Analyze the Impact.
Since its launch in 1993, Kansas sales tax and revenue bonds (STAR) have unlocked more than $1 billion in economic development financing. Each attraction financed through the program aims to bring job creation and improved quality of life to Kansas residents, yet the program’s primary goal is to create new spending in the Kansas economy by attracting tourists.
The Kansas Department of Commerce is responsible for selecting STAR bond attractions and districts, largely based on their feasibility to bring new tourism to the state.
However, the department lacks sufficient before-and-after data or consistent processes to evaluate if such attractions are actually boosting tourism. Without this information, it’s difficult to accurately determine if certain attractions will bring in the necessary revenues to pay off their bonds — and with billions of dollars at play, this absence of data could put Kansas’ economic welfare at risk.
To get a deeper understanding of the impact STAR bond attractions have on state tourism, the Kansas Legislative Division of Post Audit (LPA) conducted a performance audit of visitation data at 16 sites. With the help of StreetLight Data, LPA uncovered surprising insights on the efficacy of the attractions, and gained an in-depth understanding of how data-driven auditing can optimize the STAR bond program.
Tapping Into Tourism Trends
While the Department of Commerce received visitation projections of each selected STAR attraction amid feasibility assessments, it did not have the authority to require ongoing visitation data from attractions until 2021. As a result, LPA did not have access to any comprehensive or reliable visitation data to support its audit of the state’s completed STAR sites — leaving StreetLight to help fill in the gaps.
Using StreetLight’s Origin-Destination Metrics, LPA discovered that only three of the 16 evaluated attractions met the Department of Commerce’s tourism-related goals in 2018 and/or 2019. Interestingly, these three attractions — the Kansas Speedway, Topeka’s Heartland Park and the Hutchinson Underground Salt Museum — all shared one commonality: Unlike other STAR sites, these are unique attractions that are not otherwise available in the region.
With this data, LPA could identify a core problem with the state’s STAR attraction program: Officials may not be financing the right types of attractions for their intended goals. While some attractions like children’s parks or retail centers can improve local quality of life, the data shows they don’t necessarily draw in the intended audience of out-of-state-visitors, hindering the site’s ability to generate new revenue for the state.
Learning Hard Lessons With Hard Data
While the availability of travel data has exploded since the STAR bonds financing program was introduced, Kansas officials have not taken advantage of it to measure the impact of their investments — which is a common problem among government-funded investments. Using data to practice consistent, widespread before-and-after studies is becoming increasingly critical to measure goals and optimize spending, as LPA demonstrated in its audit.
To encourage this practice among officials, LPA drafted key recommendations to help the state better monitor the STAR bonds program. Such recommendations suggested the Department of Commerce collects consistent, comprehensive visitation data from STAR bond sites, and the Kansas Legislature considers amending the program’s goals to ensure attractions are generating the intended revenues.
The Department of Commerce questioned the methodologies and nuances of LPA and StreetLight’s assessment in response to these recommendations, though it did acknowledge the need for more comprehensive data and transparency within the STAR bonds program. Such data will soon be required under SB 124, signed into law by Kansas Gov. Kelly in April 2021.
Until then, LPA’s study remains a key lesson in the importance of data-driven decisions that are not based on optimistic projections or assumptions. It’s also a reminder for governments and agencies to remain consistent in their data assessments as time passes. By collecting and sharing relevant data, it’s possible to get ahead of challenges or reallocate resources to protect investments and economic prosperity. And when we replace our existing beliefs or political pressures with reliable data, we can unlock the opportunities that are proven to create a more prosperous economy.
Getting Transportation and Land Use to Work Together
Getting Transportation and Land Use to Work Together
Like most transportation engineering professionals, my graduate school studies were filled with learning about optimizing traffic flow: In other words, how can we move the most vehicles as fast as possible? We were even given equations to understand how to maximize volume and speed.
Fast forward a few years and I am living in the heart of Atlanta, Georgia, a city that has worked hard to maximize volume and speed on its roadways. One day, while walking through traffic to my neighborhood grocery store, I started thinking back to my graduate school days. Even though I could have driven to the store quickly on the Atlanta roads, I preferred to walk. I realized that good planning involves a lot more than just vehicular volume and speed. Transportation is sometimes more complex than I was taught.
Aligning Transportation and Land-Use Goals
On that street in Atlanta, I realized that transportation problems sometimes require additional context to fully understand and solve them. For example, those equations I learned in graduate school didn’t teach us that a person is more likely to walk next to a 25 mph roadway than a 35 mph one. Or that someone living in a high walkability area will drive fewer miles in a day. Or even how to identify and quantify something like “high walkability.”
When transportation experts step back to look at the bigger picture, they need to know how transportation fits into the greater issue of land use.
From my perspective as a solutions engineer at StreetLight, part of contextualizing transportation’s larger problems comes down to data, and how it’s used. Transportation engineers and planners often work together on big projects, but use different data to analyze and understand the issues. This can create misaligned goals and objectives — for example, a transportation expert may be looking at land use from the perspective of making streets safer, when a city engineer may be studying how to make them faster.
How to Study Larger Planning Issues
Instead, how about contextualizing larger transportation goals and objectives within land-use frameworks? We could study questions like:
How fast are people driving around school zones?
Are people living in walkable areas traveling less to get to their destinations?
Where is the best location to place bike infrastructure to connect residential areas with work destinations, while avoiding high level-of-stress routes?
Without easy tools to visualize both transportation and land-use data, these questions often end up with varied answers. Or they’re simply left unanswered.
Expand the Data Set for Answers
At StreetLight, we want to enable this bigger picture, and help both planners and transportation experts understand more than just the transportation piece of the mobility puzzle. We want to give land-use planners the ability to contextualize transportation metrics.
To do this we have partnered with UrbanFootprint, the leading software platform for sustainable city design and urban planning. UrbanFootprint understands the power that planning and mobility decisions have to affect a community’s overall livability, along with its fiscal, environmental, and public health.
StreetLight and UrbanFootprint have come together to ensure that planners can get the most out of combined transportation and land-use data.
Our transportation data is now helping support UrbanFootprint’s planning platform. This means planners can now analyze a project with the most valuable transportation data in the industry.
As always, StreetLight stands ready to support in-depth mobility analysis with our on-demand transportation metrics. But for larger planning issues that require contextual data, we are excited to bring mobility context to UrbanFootprint’s extensive data and planning toolset.
How Big Data Can Help Combat Climate Change
How Big Data Can Help Combat Climate Change
Earth Day invites us to reflect on our responsibilities on this planet, and the role(s) that individuals and businesses can play to help confront one of the greatest challenges of our time — climate change. At StreetLight Data, we know that Big Data can immeasurably enhance planning and policy for managing transportation-related greenhouse gas (GHG) emissions. In fact, it is baked right into our company mission, “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.”
According to the Intergovernmental Panel on Climate Change (IPCC), in order to minimize increasing impacts such as extreme heat, drought, and heavy precipitation, additional warming of our planet must be limited to 1.5°C. In order to meet this threshold, we must make rapid and far-reaching changes in energy, land, and infrastructure use (including transport and buildings), with deep emissions reductions in all sectors.
Some studies suggest that about 20% of these emission reductions must come from trips avoided or trips shifted — for example, from cars to trains, buses and bikes. Given that estimated greenhouse gas (GHG) emissions from the U.S. transportation sector accounted for 27% of total U.S. GHG emissions in 2010, there is still plenty of work ahead.
In addition to managing the impact of our own business operations, StreetLight provides transportation professionals with the best metrics and tools to confront the challenge. Two ways we accomplish this are by developing data-driven processes to help evaluate and manage vehicle miles traveled (VMT) emissions, and developing data analysis and visualization tools to help clients better plan for electric vehicle charger deployment and automated vehicles.
Evaluating Vehicle Miles Traveled (VMT) with Big Data
VMT — a measure of the amount of travel for all vehicles in an area over a given period of time — is widely recognized as a critical factor for understanding (and thus managing) a variety of negative transportation impacts. VMT creates wear and tear on roads and is directly related to greenhouse gas emissions (GHG), air pollution, and petroleum use. VMT is increasingly important in modern transportation regulation at both the Federal and state level, such as California’s SB 375 and SB 743, which use VMT as an indicator of regional achievement of greenhouse gas reduction and other goals.
Measuring the length of trips over time can be a better measure for transportation performance than the number of trips alone, depending upon which impact you are trying to measure. This is because for certain concerns, like greenhouse gases, the length of the trip is more important than the number of trips. For example, a ten mile trip has twice as much impact from a GHG perspective as a five-mile trip.
Using a combination of StreetLight Insight® tools including Zone Analysis, Origin-Destination, Segment Analysis, and AADT, transportation planners can estimate VMT for entire regions or for individual road segments. This data can provide quick answers to important planning and policy-related questions such as:
How does regional VMT change over time?
How does a particular area, land use, or development contribute to regional VMT?
How do short trips (personal and commercial) contribute to VMT?
How much of a region’s VMT is contributed by internal trips vs. vehicles from the surrounding region?
Using Big Data to Plan for Electric Vehicle Charger Deployment
As transportation infrastructure planners, we recognize that most vehicle charging will be done at home. But we will need convenient, cost-effective out-of-home charging to drive maximum adoption levels for EVs. Transportation analytics derived from Big Data can support better planning for deployment of EV charging infrastructure including:
Site selection, macro: Scan an entire city to find the best places for EV charging.
Site selection, micro: Analyze and validate individual potential sites.
Education and awareness: Select highly visible “activity centers” for chargers to maximize public exposure.
Right-sizing: Improve estimates of grid load and electrical cost (and V2G or other ancillary grid service applications).
Figure 1 below provides an example of a site selection macro analysis. Using analytics derived from Big Data, StreetLight can scan an entire city or region to find the best spots for EV chargers. Big Data’s flexibility allows us to define “best” in different ways, and easily run multiple scans at very low marginal cost and effort.
Figure 1: A scan of the San Francisco Bay area highlights the work neighborhoods of people who drive more than 40 miles per day, and currently live in high-hybrid adoption areas.
In addition to the out-of-the-box functionality of StreetLight Insight, custom apps and dashboards can be developed using LBS and GPS data, combined with maps of high hybrid penetration data, existing EV charging station data, and preferred utility charging locations.
These are just a few examples of how StreetLight is using Big Data to do our part. We know there is much more work to be done – and are always happy to discuss new opportunities to collaborate, and ways that we can use Big Data to improve transportation and help make the planet healthier.
