A three-hour drive is never a three-hour drive, thanks to traffic snarls, pit stops, and weather conditions. While current mapping apps are better able to predict how long it will take us to get somewhere, what if they could also recommend the best time and place for you to stop based on past traffic data? An algorithm from researchers at MIT might help real-life travelers do this.

The algorithm, which would work for map and traffic programs, would help everyone from individual commuters to massive transit systems. One key innovation is that it calculates the probability that traffic problems will arise at any point. The algorithm’s ancestors are programs used to calculate risk for NASA missions, which are more expensive and delicate than your drive to and from IKEA.

The model doesn’t just work for travelers by car, either. It can use data about how long it usually takes to travel a given stretch of road to design bus and plane schedules, optimizing trip planning for dozens or hundreds of passengers at a time.

Right now, the algorithm exists as a concept, and hasn’t yet been integrated into a travel app for real-world testing. Still, it’s kind of comforting to know that soon, a computer might tell me when and where I should eat and use the restroom in order to speed up my trip and miss typical traffic snarls.

NEW ALGORITHM CAN HELP PLAN YOUR PEE BREAKS BETTER ON ROAD TRIPS [Popular Science]

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