GM coined the term “range anxiety” to describe how drivers felt when the battery in an EV began ran low, and it’s since become a major sticking point in the adoption of electric cars. Researchers from North Carolina State University have developed a more accurate range estimation software that could alleviate or eliminate range anxiety altogether.

One of the issues facing electric cars is that the estimated range can vary a lot depending on all sorts of circumstances, many of them outside the driver’s control. While you don’t have to have the air conditioning blasting the whole ride, an unexpected hill or traffic jam can reduce your expected range substantially. Unfortunately the software used to predict your range relies on the average energy consumption of the last few miles of driving.

But the research team led by Dr. Habiballah Rahimi-Eichi, a postdoctoral researcher at NC State, used a predictive technique to better estimate range. You enter your destination, and the software sorts through a number of static and fluid factors, like hills or traffic congestion, to estimate how much energy it will take to complete your trip.

“By plugging in the destination, our software looks at traffic data, whether you’ll be on the highway or in the city, weather, road grade, and other variables,” says Rahimi-Eichi. This predictive, big-data approach is a significant step forward, reducing the range estimation error to a couple of miles. In some case studies, we were able to get 95 percent range estimation accuracy.”

While this system requires input on the part of the driver, as compared to the passive system in current EVs, the added accuracy could be a major selling point for next-gen vehicles. As electric vehicles add more and more range though, range anxiety will become less and less of an issue.