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Autonomous Driving Predictive Systems

MIT Researchers Created a System to Predict Bad Driving

— November 19, 2019 — Autos
MIT researchers from CSAIL, the Computer Science and Artificial Intelligence Laboratory, recently created an autonomous driving system that can better account for poor driving from cars around it. In order to create the system, the MIT researchers used several principles form social psychology to train the system to identify certain actions as selfish or selfless.

After the system was exposed to different driving styles it was able to predict other driver's behaviors more accurately. The system had a 25% increase in its ability to predict if other cars would merge lanes or make an ill-advised turn.

The team of MIT researchers will now look to adapt the system to be used with pedestrians and cyclists.


Image Credit: Shutter stock
Trend Themes
1. Autonomous Driving Systems - Opportunity for disruptive innovation in creating more accurate and reliable autonomous driving systems that can account for poor driving behaviors.
2. Predictive Systems - Opportunity for disruptive innovation in developing predictive systems that can accurately anticipate and predict the behavior of other drivers.
3. Influencing Driving Behaviors - Opportunity for disruptive innovation in developing systems that can influence and improve the driving behaviors of human drivers through social psychology principles.
Industry Implications
1. Automotive - Opportunity for disruptive innovation in the automotive industry to create advanced autonomous driving systems that can better account for poor driving behaviors of other cars.
2. Artificial Intelligence - Opportunity for disruptive innovation in the artificial intelligence industry to develop predictive systems that can accurately anticipate and predict the behavior of other drivers.
3. Transportation - Opportunity for disruptive innovation in the transportation industry to improve overall driving behaviors by developing systems that can influence and shape the behavior of human drivers.
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