Researchers from a university in Massachusetts are developing new intelligent transportation system (ITS) algorithm that takes into account models of human driving behavior to warn drivers of potential collisions, and ultimately takes control of the vehicle to prevent a crash. A common challenge for ITS developers is designing a system that is safe without being overly conservative. It is tempting to treat every vehicle on the road as an agent playing against the vehicle, but with this approach the system is overly sensitive. The researchers reasoned that driving actions fall into two main modes: braking and accelerating. Depending on which mode a driver is in at a given moment, there is a finite set of possible places the car could be in the future, whether a tenth of a second later or a full 10 seconds later. This set of possible positions, combined with predictive models of human behavior – for example, when and where drivers slow down or speed up around an intersection – all are going into developing the new algorithm. The result is a program that is able to compute, for any two vehicles on the road nearing an intersection, a defined area in which two vehicles are in danger of colliding. The ITS-equipped car then engages in a sort of game-theoretic decision, in which it uses information from its onboard sensors as well as roadside and traffic-light sensors to try to predict what the other car will do, reacting accordingly to prevent a crash. When both cars are ITS-equipped, the ‘game’ becomes a cooperative one with both cars communicating their positions and working together to avoid a collision. The researchers have already begun to test their system in full-size vehicles with human drivers; future work will focus on incorporating driver reaction-time data to refine when the system must actively take control of the car and when it can merely provide a passive warning to the driver.
http://web.mit.edu/newsoffice/2011/smart-cars-0614.htmlhttp://web.mit.edu
