StreetLight Data’s EV Mode Equips Mobility Planners to Build EV Infrastructure Efficiently

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Electric Vehicle Mode analytics service from StreetLight Data can provide useful insights to cities that are looking for better handle to roll out electric vehicle charging infrastructure.

Launched recently, EV Mode provides transportation planners detailed data to assist with equitable development of EV infrastructure. It comprises data about locations where EV drivers travel, stop and charge; the times they drive in business and residential districts; and the speed they drive with, and how far they drive to find a charging station and how driving patterns change over time.

StreetLight gathers real-time data from connected cars and trucks, smartphones, road sensors and weather forecasts, smartphones, as well as data from GPS navigation – and location –based services. StreetLight also includes land use and demographic data, up to the city-block level. The machine learning algorithm of StreetLight helps formulate a statistically sound picture of everything that is moving, stated a senior executive at StreetLight. This includes e-bikes, bicycles, and pedestrians besides vehicles.

Cities deciding where to build EV charging stations can use the company’s service to evaluate existing EV traffic, compare gas-driven traffic to EV traffic, obtain data on where people are charging and establish where demand is likely to increase to ensure that charges are positioned equitably.

The metrics of the company have been leveraged by a number of local and state transportation departments, including those in Maine, Massachusetts, Florida, Texas, Washington as well as Orlando, Los Angeles, Indianapolis and others. StreetLight data was used by San Jose, California in their decision support system – a software tool that uses big data and analytics to assist city officials establish the next best strategy to improve mobility.

Edward Turner

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