Our rented SUV (Chevrolet Equinox) in Yosemite National Park, California. William Warby
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It’s time for vacation. Everyone piles into the car and heads over the river and through the woods to Grandmother’s house 488 miles away. Google says it will take you seven and a half hours to get there. Google lies.

Those seven and a half hours only account for drive time, not the stops for food and pee breaks that all long-distance road trips must include. (PSA: For a road trip activity, you can check the color of your pee because staring into a rest stop toilet is always fun! Right?)

While apps like Google Maps are starting to incorporate traffic delays into directions, that can be hard to determine hours before you leave. In the future, however, travel planning could get even better with the help of algorithms.

MIT professor Brian Williams (No, not that Brian Williams) is working with a group of researchers to develop planning algorithms that can incorporate all of your travel needs–from when you have to be at the airport to when you should stop for lunch to stay on schedule. It could even be used by city planners to schedule bus lines or by airlines to schedule flights.

The algorithm is still very much in development. “This is basic research at this point,” Williams told Dell’s Tech Page One. “We have focused on developing algorithms and a proof of concept. Significant work remains to develop this into a mature product.”

Eventually, though, the hope is that you could put in your destination (Grandma’s house), any stops you’d like to make (lunch around noon at a Wendy’s), and when you want to get there. The program will come up with suggestions for you, offering alternative schedules (Panera at 1:00 for lunch) that might give you a better chance of getting there on time given traffic conditions. If there are delays, or you have to stop for gas, then the program would re-calculate in real time, trying to keep to your original travel goals.

Williams has been working with this type of algorithm for a while; he helped develop the Remote Agent AI system that NASA used to control a space probe back in 1999. Now, the same research that helped a spacecraft adjust to space weather might help people plan trips much closer to earth.

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