Self-driving cars are often thought of as superior to human drivers, but humans may still be able to teach the machines a thing or two. Autonomous cars aren't particularly good at executing lane changes, and MIT decided the solution to this problem was an algorithm that allows self-driving cars to act more like human beings.

Researchers at MIT's Computer Science and Artificial Intelligence Laboratory developed the new algorithm because they felt current lane-change algorithms were inadequate. Most are based on detailed statistical models that are too complex for making decisions on the fly, according to MIT. Others force the car to act very conservatively, possibly avoiding lane changes altogether.

The MIT algorithm actually allows more aggressive behavior on the part of autonomous cars. That may not be what some people want to hear now that a self-driving car has been involved in a fatal crash, but it may be necessary for cars to negotiate thick traffic in cities like New York. The algorithm also uses less information, allowing cars to make quicker decisions, according to MIT.

"The motivation is, 'What can we do with as little information as possible?'" Alyssa Pierson, a postdoc at CSAIL and first author on a paper detailing the algorithm, said in a statement. "How can we have an autonomous vehicle behave as a human driver might behave?"