Innovative analysis tool paves the way for better mobility for all

Mobility Energy Productivity tool helps decision makers visualize transportation equity gaps and find solutions

How long does it take you to get to work or school? The answer varies widely for many Americans, depending on factors such as where they live and whether they own a car. Even in densely populated cities like New York, a day’s routine can involve hours of travel time.

Many essential trips also gobble up fuel and a disproportionate share of household income. When it takes too long, costs too much, or uses a lot of energy to reach key places like jobs and healthcare, that’s shoddy mobility, and it affects everyone. Traffic jams alone cost the United States billions of dollars in lost time and wasted fuel every year. Meanwhile, excessive pollution from inefficient travel undermines climate goals and deteriorates air quality.

While insufficient mobility and accessibility have a wide impact, the burden falls most heavily on low-income areas, which generally have longer journeys, fewer transport options and higher transport costs. Mobility equity issues affect the quality of life of millions of people, from rural areas to urban centres.

Many parts of the United States lack affordable, accessible, and efficient travel options. The Mobility Energy Productivity tool offers decision makers a way to assess the mobility quality of a region.

Researchers from the National Renewable Energy Laboratory (NREL) of the United States Department of Energy have developed an innovative method to quantify and understand this problem: the Mobility Energy Productivity (MEP) tool. MEP distills three major components of mobility (time, cost, and energy) into a simple, easy-to-read score. This score can quantify the effectiveness of the connectivity provided by one or more modes of travel (such as biking, car, or public transit) for a given geographic area, from a small neighborhood to a large state. MEP can also analyze mobility quality for specific groups based on characteristics such as income, age and vehicle ownership.

A New Window on Mobility Equity

“With MEP, we can quantify disparities in mobility and access for underserved population segments,” said Venu Garikapati, senior transport data researcher and one of MEP’s creators. “We also showed possible improvements in mobility equity based on specific scenarios, such as high levels of carpooling.”

The MEP algorithm quantifies the total number of destinations in an area that people can reach in a certain amount of time. For a given square kilometer, the MEP tool calculates available opportunities across four modes (car, walk, bike and public transport), four travel time thresholds (10, 20, 30 and 40 minutes) and five destination types distinct (schools, hospitals, restaurants, recreational facilities and stores), in addition to quantifying access to jobs.

A city’s MEP score depends on geography, building density, road network, availability of modes, travel patterns, and the efficiency of the entire transport system in connecting people to their destinations. Similar to a stock index, the score has no upper limit and can be calibrated to a base year of choice and then tracked as a percentage increase or decrease from the baseline. Locations that require less travel time, money, and energy to reach are weighted more heavily than those generally further away, which require more resources to reach.

MEP equates a variety of travel dimensions into an easy-to-read score for a geographic area. Users can analyze, together or separately, modes such as cycling or public transport; destination types such as jobs and health care; and socio-demographic factors such as age or income.

The MEP can also analyze the efficiency of new energy-efficient modes (such as electric vehicles) or cost-effective modes (such as shared mobility services) within a given mobility system. Its flexibility, combined with the simplicity of having a single metric, makes MEP a powerful tool for government agencies, businesses, and other organizations interested in improving transportation options. Several state transportation agencies, including those in Colorado, Delaware, and Florida, are evaluating the MEP tool to aid in infrastructure investment decisions.

The Delaware Department of Transportation, for example, is conducting a trial of MEP for possible integration into its planning process, which includes criteria for mobility, access, and economic justice.

“Basic research like NREL’s is absolutely essential – and having the opportunity to work with practitioners like us to try to implement the insights from that research is even more critical,” said Anson Gock, a planner at the Delaware Department of Transportation.

StreetLight Data, which provides data and information to hundreds of planning agencies and transportation companies across North America, is collaborating with NREL to explore the viability of integrating MEP with the existing suite of business metrics and tools.

“Transportation professionals are increasingly in need of comprehensive data, tools and metrics to ensure they are incrementally improving the quality of mobility in their communities,” said Laura Schewel, Founder and CEO of StreetLight. . “MEP represents an important tool to address these challenges.

Pixel-level MEP scores are deconstructed according to mode and destination dimensions.

Powerful flexibility for transportation analysis

One or more parameters can be adjusted to refine an MEP analysis. A focus on transit alone, for example, will reveal neighborhoods where commuters save time, money and energy by taking the bus or train. It is possible to compare access to employment opportunities between low- and high-income populations or to see how and where mobility varies according to vehicle ownership.

Consider the Chicago, Illinois MEP maps for two types of households: those without a vehicle and those with at least one vehicle for every driver. The difference is striking: the quality of mobility for households without a vehicle is one tenth of that enjoyed by residents with their own car. The average journey made by households without a vehicle is around twice as long – around 40 minutes – compared to households that have as many or more vehicles as drivers (or “sufficiently equipped” households). Households without a vehicle also have far fewer destinations accessible on foot, by bike or by public transport.

Chicago’s citywide MEP scores—220 for households without a vehicle (left) and 1,918 for households with sufficient vehicle (right)—show the contrast in mobility quality. To create city-wide MEP scores, researchers use the individual MEP score for each location in a city and calculate a weighted average taking into account the population at each location. The resulting single score captures the quality of mobility where people live across the city.

Policy makers can use this information to determine where disparities are greatest and direct investments to those communities. Analyzes like these can be performed for any demographic dimension (such as income level or vehicle ownership) or a combination thereof.

“MEP opens up another way of thinking about mobility,” said Christopher Hoehne, mobility systems researcher with the MEP team. “Seeing mapped analysis inspires thinking about community planning, where important destinations are located. It also reveals opportunities to connect different modes of travel, such as cycling with public transport.

Personal travel in America has always been very car-centric, and the infrastructure of our cities reflects that, which is why we’ve tended to focus primarily on improving the efficiency and affordability of driving.” , said Hoehne. “But increasingly, we’re starting to see that increasing our focus on other modes of travel provides a way to integrate equity and sustainability considerations into future transport planning. Sometimes this involves combining different modes together.

Members of the NREL Transport Data Research Team (left to right) Venu Garikapati, Ambarish Nag, Chris Hoehne, Shivam Sharda, Stan Young and Robert Fitzgerald developed the Mobility Energy Productivity tool, which can help decision-makers to visualize the equity gaps in transport – and find solutions. Photo by Werner Slocum, NREL

Typical accessibility research in transportation focuses heavily on time and cost, Hoehne said, adding that the team spent time developing the tool and the underlying metric, to focus on the new aspect of energy, but also plans to extend the MEP to capture even more aspects of the quality of mobility.

The MEP team is currently reviewing emissions data, for example, to better reflect greenhouse gases and factor air pollutant criteria directly into MEP calculations. In the future, the tool will also be able to integrate additional factors such as safety and quality of infrastructure.

“We are only beginning to realize the full potential of what MEP can do,” Garikapati said, “and how it can be used to create healthier, more convenient mobility for everyone.”

Learn more about NRELs transport and mobility research. And sign up for NREL’s quarterly transportation and mobility research newsletter, Sustainable mobility mattersto receive the latest news.

Originally published on NREL. By Christina Nunez


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