Innovative Analysis Tool Opens Path To Better Mobility For All

How long does it take you to get to work or school? The answer varies widely for many Americans, depending on factors like where they live and whether they own a car. Even in densely populated cities like New York, a day’s routine can involveMany essential trips also gobble up fuel and an outsized share of household income. When it takes too long, costs too much, or consumes lots of energy to reach key places like jobs and healthcare, that is poor quality of mobility—and it affects everyone.

The MEP algorithm quantifies the total number of destinations in an area that people can reach within a certain amount of time. For any given square kilometer, the MEP tool calculates available opportunities across four modes , four travel time thresholds , and five distinct destination types , in addition to quantifying access to jobs.

MEP can also analyze the effectiveness of newer energy-efficient modes or cost-efficient modes within a given mobility system. Its flexibility, combined with the simplicity of having a single metric, makes MEP a powerful tool for government agencies, companies, and other organizations interested in improving transportation options.

StreetLight Data, which provides data and insights to hundreds of planning agencies and transportation firms across North America, is collaborating with NREL to explore the viability of integrating MEP with the company’s existing suite of metrics and tools. Consider MEP maps of Chicago, Illinois, for two types of households: those with no vehicles and those with at least one vehicle for each driver. The difference is stark: the quality of mobility for the no-vehicle households is one-tenth of that enjoyed by residents with their own cars. The average trip made by zero-vehicle households is about twice as long—about 40 minutes—compared to households that have as many or more vehicles than drivers .

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